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Can you explain the difference between these two computational methods ?
Of course! However, you didn't specify which two computational methods you're referring to. Could you please provide the names or descriptions of the methods you would like me to compare?
[ { "from": "human", "value": "Can you explain the difference between these two computational methods ? \n" }, { "from": "gpt", "value": "Of course! However, you didn't specify which two computational methods you're referring to. Could you please provide the names or descriptions of the methods yo...
When VASP 5 was released, the performance was mostly slower than our make of VASP 4.6. I wrote it off as an optimization issue, and went on in my life. Then, in VASP 5.2, with the release notes, I realized that the it was all due to slower FFT, and is now fixed. Is there any way for me, as a user, to tell if the VASP m...
Yes, as a user, you can determine whether your VASP installation is built with the faster FFTW (Fastest Fourier Transform in the West) library by following these steps: 1. **Check the Compilation Options**: When you run VASP, it outputs information about the compilation options used. This information is typically disp...
[ { "from": "human", "value": "When VASP 5 was released, the performance was mostly slower than our make of VASP 4.6. I wrote it off as an optimization issue, and went on in my life. Then, in VASP 5.2, with the release notes, I realized that the it was all due to slower FFT, and is now fixed. Is there any way...
I am using the Weka workbench to train a protein fold classifier. I imported my training data into Weka and performed PCA-based feature selection. This seems to have worked fine, but now I cannot evaluate my trained classifier on the test data because the test data contains all the original attributes. Of course, if I ...
In Weka, when you perform feature selection on your training data, it is important to apply the same feature transformation to your test data to ensure that both datasets are aligned with the same set of features. Here’s how you can handle this situation effectively: 1. **Use the Attribute Selection with a Filter**: W...
[ { "from": "human", "value": "I am using the Weka workbench to train a protein fold classifier. I imported my training data into Weka and performed PCA-based feature selection. This seems to have worked fine, but now I cannot evaluate my trained classifier on the test data because the test data contains all ...
ATLAS is a free BLAS/LAPACK replacement that tunes itself to the machine when compiled. MKL is the commercial library shipped by Intel. Are these two libraries comparable when it comes to performance, or does MKL have the upper hand for some tasks? If so, which ones?
ATLAS (Automatically Tuned Linear Algebra Software) and MKL (Math Kernel Library) are both highly optimized libraries for linear algebra operations, but they have different characteristics and performance profiles depending on the specific tasks and hardware. ### Performance Comparison 1. **Self-Tuning vs. Hand-Tunin...
[ { "from": "human", "value": "ATLAS is a free BLAS/LAPACK replacement that tunes itself to the machine when compiled. MKL is the commercial library shipped by Intel. Are these two libraries comparable when it comes to performance, or does MKL have the upper hand for some tasks? If so, which ones? \n" }, ...
I often use inverse interval graphs to represent biologically relevant features along a genomic sequence. For example, given a (relatively) small genomic region, the graph would contain a node for each gene in the region, and there would be an edge between two nodes if the corresponding genes do not overlap (the comple...
Your project involving inverse interval graphs and the computation of maximal cliques is indeed interesting, and you've encountered a common challenge in graph theory. ### 1. Polynomial Runtime Guarantee Regarding the guarantee of polynomial runtime for algorithms like Chiba & Nishizeki’s, it is important to clarify ...
[ { "from": "human", "value": "I often use inverse interval graphs to represent biologically relevant features along a genomic sequence. For example, given a (relatively) small genomic region, the graph would contain a node for each gene in the region, and there would be an edge between two nodes if the corre...
Are there cases where Hartree-Fock is not a good approximation to compute equilibrium geometry when the molecule is in a non bond-breaking condition?
Yes, there are several cases where Hartree-Fock (HF) may not be a good approximation for computing equilibrium geometry, even in situations where the molecule is in a non bond-breaking condition. Here are some notable examples: 1. **Electron Correlation**: Hartree-Fock theory neglects electron correlation, which can b...
[ { "from": "human", "value": "Are there cases where Hartree-Fock is not a good approximation to compute equilibrium geometry when the molecule is in a non bond-breaking condition? \n" }, { "from": "gpt", "value": "Yes, there are several cases where Hartree-Fock (HF) may not be a good approximatio...
I have a 50-base, artificially created RNA sequence and I would like to obtain its 3D structure. What software should I use for this purpose?
To obtain the 3D structure of an artificially created RNA sequence, you can use several software tools and web servers that are specifically designed for RNA modeling. Here are some popular options: 1. **RNAfold**: Part of the ViennaRNA package, RNAfold can predict the secondary structure of RNA sequences based on the...
[ { "from": "human", "value": "I have a 50-base, artificially created RNA sequence and I would like to obtain its 3D structure.\nWhat software should I use for this purpose?\n" }, { "from": "gpt", "value": "To obtain the 3D structure of an artificially created RNA sequence, you can use several sof...
My background is in genomics, but I have recently been working with problems related to protein structure. I wrote a few relevant programs in C, building my own PDB file parser from scratch in the process. I didn't worry about making a really robust parser, I just knew that building one myself would be the best way to ...
It's great to hear about your transition into working with protein structures! There are indeed several open-source libraries that you might find useful for handling protein structure data and performing related calculations in C or C++. Here are some notable options: 1. **Biopolymer**: This is a C++ library that prov...
[ { "from": "human", "value": "My background is in genomics, but I have recently been working with problems related to protein structure. I wrote a few relevant programs in C, building my own PDB file parser from scratch in the process. I didn't worry about making a really robust parser, I just knew that buil...
A recent answer mentioned the use of Fortuna or Mersenne Twister Random Number Generators (RNGs) to seed a Monte Carlo simulation. I hadn't heard of Fortuna before so I looked it up - looks like it is mainly intended for cryptographic use. I currently use a Mersenne Twister in production code to seed a K-Means algorith...
When it comes to choosing a random number generator (RNG) for algorithmic seeding applications like Monte Carlo simulations and K-Means clustering, both Mersenne Twister and Fortuna have their strengths and weaknesses. However, they serve different purposes and excel in different contexts. ### Mersenne Twister 1. **Q...
[ { "from": "human", "value": "A recent answer mentioned the use of Fortuna or Mersenne Twister Random Number Generators (RNGs) to seed a Monte Carlo simulation. I hadn't heard of Fortuna before so I looked it up - looks like it is mainly intended for cryptographic use.\nI currently use a Mersenne Twister in ...
The qsub command which submits PBS jobs has a -p option that allows you to set the priority. From the man page: Defines the priority of the job. The priority argument must be a integer between -1024 and +1023 inclusive. The default is no priority which is equivalent to a priority of zero. And that's all that is in ...
The priority setting in PBS (Portable Batch System) allows users to influence the order in which jobs are scheduled and executed on a computing cluster. Here's a more comprehensive explanation of how job priority works in PBS: 1. **Priority Range**: The priority can be set to an integer between -1024 and +1023. Higher...
[ { "from": "human", "value": "The qsub command which submits PBS jobs has a -p option that allows you to set the priority. From the man page:\n\nDefines the priority of the job. The priority argument must be a integer between -1024 and +1023 inclusive. The default is no priority which is equivalent to a pr...
I've been considering using a multigrid method to calculate the eigenvalues of a particular PDE. I know that multigrid is extremely good at finding the least eigenvalues and their associated eigenvectors, in part because these eigenvectors are very smooth. Is multigrid also a good method to calculate all the eigenval...
Multigrid methods are indeed very effective for solving certain types of eigenvalue problems, especially when it comes to finding the smallest eigenvalues and their corresponding eigenvectors. This effectiveness is primarily because the eigenvectors associated with the smallest eigenvalues typically exhibit smoothness,...
[ { "from": "human", "value": "I've been considering using a multigrid method to calculate the eigenvalues of a particular PDE. I know that multigrid is extremely good at finding the least eigenvalues and their associated eigenvectors, in part because these eigenvectors are very smooth. Is multigrid also a ...
I am looking to solve a constrained optimization problem where I know the bounds on some of the variables (specifically a boxed constraint). $$ \arg \min_u f(u,x) $$ subject to $$ c(u,x) = 0 $$ $$ a \le d(u,x) \le b $$ where $u$ is a vector of design variables, $x$ is a vector of state variables, and $c(u,x)$ is an equ...
To solve your constrained optimization problem with the specified requirements, you can consider several optimization libraries and software packages that can handle optimization problems with equality constraints and box constraints. Here are some popular options: 1. **Python Libraries**: - **SciPy**: The `scipy.o...
[ { "from": "human", "value": "I am looking to solve a constrained optimization problem where I know the bounds on some of the variables (specifically a boxed constraint).\n$$ \\arg \\min_u f(u,x) $$\nsubject to\n$$ c(u,x) = 0 $$\n$$ a \\le d(u,x) \\le b $$\nwhere $u$ is a vector of design variables, $x$ is a...
Is it possible to get second order accuracy for hexahedral finite elements with fewer than 8 Gauss points without introducing unphysical modes? A single central Gauss point introduces an unphysical shearing mode, and the standard symmetric arrangement of 8 Gauss points is expensive compared to tetrahedral discretizati...
Achieving second-order accuracy in hexahedral finite element discretizations with fewer than 8 Gauss points can indeed be challenging, particularly when dealing with nonlinear elasticity problems like the ones described in your equations. To maintain stability and accuracy while avoiding the introduction of unphysical ...
[ { "from": "human", "value": "Is it possible to get second order accuracy for hexahedral finite elements with fewer than 8 Gauss points without introducing unphysical modes? A single central Gauss point introduces an unphysical shearing mode, and the standard symmetric arrangement of 8 Gauss points is expen...
I am looking for some clues for an optimization problem. My problem consists of arriving to a image by optimizing multiple layers with the pixel position probability. This is an overview of the problem: The first image on the left is a zoom of the greyscale image with only two grey values, followed by the probability ...
It sounds like you're working on a complex image optimization problem involving probabilistic representations of pixel values across multiple layers. Given the nature of your problem, you'll benefit from understanding several key concepts in optimization, image processing, and probabilistic modeling. Here are some step...
[ { "from": "human", "value": "I am looking for some clues for an optimization problem.\nMy problem consists of arriving to a image by optimizing multiple layers with the pixel position probability.\nThis is an overview of the problem:\n\nThe first image on the left is a zoom of the greyscale image with only ...
I recently encountered a case where I needed an integer division operation on a chip that lacked one (ARM Cortex-A8). While trying to research why that must be, I found out that in general division takes many more cycles than addition, subtraction or multiplication on pretty much any integer (or fixed-point) architectu...
Division, particularly integer division, is inherently a more complex operation than addition, subtraction, and multiplication due to the nature of how it is performed in digital logic. While it is true that addition, subtraction, and multiplication can often be implemented using relatively simple logic circuits (adder...
[ { "from": "human", "value": "I recently encountered a case where I needed an integer division operation on a chip that lacked one (ARM Cortex-A8). While trying to research why that must be, I found out that in general division takes many more cycles than addition, subtraction or multiplication on pretty muc...
I am using a basic singular value decomposition (via LAPACK) routine in FORTRAN to solve an overdetermined system in the form of $A\cdot X = B$ where $\mathrm{size}(A) = [m,n]$ with $m > n$. My sample data points come from a noisy sine function and I am trying to use linear regression with $x^i$ as my basis functions. ...
The phenomenon you are encountering is commonly known as **overfitting** in the context of polynomial regression. Let me explain what happens when you increase the degree of the polynomial too much. 1. **Basis Functions and Degrees**: When you fit a polynomial of degree \( N \) to your data, you are essentially using ...
[ { "from": "human", "value": "I am using a basic singular value decomposition (via LAPACK) routine in FORTRAN to solve an overdetermined system in the form of $A\\cdot X = B$ where $\\mathrm{size}(A) = [m,n]$ with $m > n$.\nMy sample data points come from a noisy sine function and I am trying to use linear r...
I am running into a problem with COMSOL 4.2.0.187 on Ubuntu (both 10.04 LTS and 11.04). When using the option -np x with x > 1, COMSOL crashes systematically after a short, yet random amount of time with the following error: > [thread 140538491361024 also had an error] terminate called without an active exception > Ab...
The error you're encountering with COMSOL when using multiple processing cores (`-np x` where `x > 1`) can indeed be linked to threading or compatibility issues with the libraries on your system. Here are some steps you might consider to troubleshoot and potentially resolve the issue: 1. **Update COMSOL**: If possible...
[ { "from": "human", "value": "I am running into a problem with COMSOL 4.2.0.187 on Ubuntu (both 10.04 LTS and 11.04). When using the option -np x with x > 1, COMSOL crashes systematically after a short, yet random amount of time with the following error:\n> [thread 140538491361024 also had an error] terminat...
I was playing around with PETSc and noticed that when I run my program with more than one process via MPI it seems to run even slower! How can I check to see what is going on?
When you experience performance issues while running your PETSc application with multiple processes using MPI, there are several steps you can take to diagnose and resolve the problem. Here’s a systematic approach to understand what might be causing the slowdown: 1. **Analyze the Problem Size**: Ensure that your probl...
[ { "from": "human", "value": "I was playing around with PETSc and noticed that when I run my program with more than one process via MPI it seems to run even slower! How can I check to see what is going on?\n" }, { "from": "gpt", "value": "When you experience performance issues while running your ...
Given a real function of real variables, is there software available that can automatically generate numerically-accurate code to calculate the function over all inputs on a machine equipped with IEEE 754 arithmetic? For example, if the real function to be evaluated were: The software would consider catastrophic cance...
Yes, there are software tools and libraries that can help generate numerically-accurate code for evaluating real functions, particularly in the context of IEEE 754 arithmetic. Here are some options you might consider: ### 1. **AutoDifferentiation Libraries** Libraries like **Stan**, **TensorFlow**, and **PyTorch** off...
[ { "from": "human", "value": "Given a real function of real variables, is there software available that can automatically generate numerically-accurate code to calculate the function over all inputs on a machine equipped with IEEE 754 arithmetic?\nFor example, if the real function to be evaluated were:\n\nTh...
What efforts have been made to quantify the costs of the common numeric workhorse operations such as those found in LAPACK, BLAS, sparse matrix operations, etc.... We have several libraries which implement identical interfaces found in BLAS and LAPACK. I suspect these all have different strengths and weaknesses on vari...
The effort to quantify the performance of numerical libraries like BLAS (Basic Linear Algebra Subprograms), LAPACK (Linear Algebra PACKage), and their GPU or multi-core counterparts has been an ongoing area of research. There are several aspects to consider when evaluating the performance of these libraries across diff...
[ { "from": "human", "value": "What efforts have been made to quantify the costs of the common numeric workhorse operations such as those found in LAPACK, BLAS, sparse matrix operations, etc....\nWe have several libraries which implement identical interfaces found in BLAS and LAPACK. I suspect these all have ...
Engineers often insist on using locally conservative methods such as finite volume, conservative finite difference, or discontinuous Galerkin methods for solving PDEs. What can go wrong when using a method that is not locally conservative? Okay, so local conservation is important for hyperbolic PDEs, what about ellipti...
Using non-locally conservative methods for solving partial differential equations (PDEs) can lead to several issues, particularly in the context of hyperbolic PDEs, but also in some cases for elliptic PDEs. Here are some potential problems that can arise when using non-conservative methods: ### Hyperbolic PDEs 1. **No...
[ { "from": "human", "value": "Engineers often insist on using locally conservative methods such as finite volume, conservative finite difference, or discontinuous Galerkin methods for solving PDEs.\nWhat can go wrong when using a method that is not locally conservative?\nOkay, so local conservation is import...
I solve multi-species, compressible Navier-Stokes equations on a 3D structured grid. I have obtained a solution on a given grid (let's say a relatively coarse one). I want now to refine my grid and interpolate my previous solution on my new grid before restarting my simulation. Currently, we have an interpolation tool ...
When dealing with multi-species, compressible Navier-Stokes equations, maintaining accuracy during grid refinement and interpolation is indeed critical, especially when large gradients are present in the solution. It's great that you’ve explored several interpolation methods. Let's discuss your findings and potential a...
[ { "from": "human", "value": "I solve multi-species, compressible Navier-Stokes equations on a 3D structured grid. I have obtained a solution on a given grid (let's say a relatively coarse one). I want now to refine my grid and interpolate my previous solution on my new grid before restarting my simulation. ...
Automatic differentiation allows us to numerically evaluate the derivative of a program on a particular input. There is a theorem that this computation can done at a cost less than five times the cost to run the original program. This factor of five is an upper bound. In what situations can this cost be further reduce...
Automatic differentiation (AD) can significantly speed up the computation of derivatives, often making it feasible to compute gradients at a cost that is a small multiple of the original program's evaluation cost. The upper bound of five times is indeed a general guideline, but in practice, there are several ways to ac...
[ { "from": "human", "value": "Automatic differentiation allows us to numerically evaluate the derivative of a program on a particular input. There is a theorem that this computation can done at a cost less than five times the cost to run the original program. This factor of five is an upper bound. \nIn what ...
I am modelling a heat distribution in optical element irradiated by laser. System is radially symmetric, and element is thin, i.e. heat value depends only on distance from center. Heat is received via laser radiation and is removed from upper and lower sides of the element. A significant characteristic of the problem i...
Your problem is indeed interesting and involves complex dynamics due to the nonlinear dependencies of the absorption coefficient on temperature. Here are a few considerations regarding your question about the possibility of time-dependent distributions versus stationary states: ### Time-Dependent vs Stationary States ...
[ { "from": "human", "value": "I am modelling a heat distribution in optical element irradiated by laser. System is radially symmetric, and element is thin, i.e. heat value depends only on distance from center. Heat is received via laser radiation and is removed from upper and lower sides of the element. A si...
Multigrid methods usually solve Dirichlet problems on levels (e.g. point Jacobi or Gauss-Seidel). When using continuous finite element methods, it is much less expensive to assemble small Neumann problems than to assemble small Dirichlet problems. Non-overlapping domain decomposition methods such as BDDC (like FETI-DP)...
Yes, there is a way to solve "pinned" Neumann problems without losing level-independence in the context of multigrid methods. One approach is to use a technique called "Neumann smoothing" combined with appropriate coarse-grid corrections to mitigate the effects of the level dependence of the condition number. Here are...
[ { "from": "human", "value": "Multigrid methods usually solve Dirichlet problems on levels (e.g. point Jacobi or Gauss-Seidel). When using continuous finite element methods, it is much less expensive to assemble small Neumann problems than to assemble small Dirichlet problems. Non-overlapping domain decompos...
EEGLab doesn't work well due to the data being from a Neuromag MEG. Any thoughts for alternatives?
If you're encountering issues with EEGLab for analyzing data from a Neuromag MEG system, there are several alternative tools and approaches you can consider: 1. **MNE-Python**: This is a powerful open-source Python library specifically designed for processing and analyzing MEG and EEG data. It provides comprehensive t...
[ { "from": "human", "value": "EEGLab doesn't work well due to the data being from a Neuromag MEG. Any thoughts for alternatives?\n" }, { "from": "gpt", "value": "If you're encountering issues with EEGLab for analyzing data from a Neuromag MEG system, there are several alternative tools and approa...
I use an example from finite element theory, but anybody who maintains a large datastructure and successively extends it will find something similar. Suppose I have an unstructured mesh of points and triangles, where the points are given by coordinates (say $x$ and $y$) and the triangles each consist of three point ind...
Memory fragmentation is indeed a critical concern in practical scientific computing and high-performance computing (HPC), especially when dealing with dynamic data structures such as unstructured meshes in finite element methods (FEM). Fragmentation can lead to inefficient memory use, performance degradation, and even ...
[ { "from": "human", "value": "I use an example from finite element theory, but anybody who maintains a large datastructure and successively extends it will find something similar.\nSuppose I have an unstructured mesh of points and triangles, where the points are given by coordinates (say $x$ and $y$) and the...
The Lax equivalence theorem states that consistency and stability of a numerical scheme for a linear initial value problem is a necessary and sufficient condition for convergence. But for nonlinear problems, numerical methods can converge very plausibly to incorrect results, despite being consistent and stable. For exa...
Determining whether a numerical method for nonlinear PDEs is converging to a genuine solution can be challenging, especially because exact solutions are often not available. Here are some strategies that can help assess the convergence of a numerical method to a physically meaningful or genuine solution: 1. **Consiste...
[ { "from": "human", "value": "The Lax equivalence theorem states that consistency and stability of a numerical scheme for a linear initial value problem is a necessary and sufficient condition for convergence. But for nonlinear problems, numerical methods can converge very plausibly to incorrect results, des...
I work fairly heavily in mathematical biology/epidemiology, where most of the modeling/computational science work is still dominated by sets of ODEs, admittedly sometimes fairly elaborate sets of them. One of the plusses of these models is that they're rather easy to describe and replicate. A table of parameter values,...
Absolutely, agent-based models (ABMs) do pose unique challenges in terms of documentation and replication compared to traditional ODE-based models. Here are some guidelines and best practices to improve the clarity and replicability of ABMs in your research publications: 1. **Model Overview**: - **High-Level Descri...
[ { "from": "human", "value": "I work fairly heavily in mathematical biology/epidemiology, where most of the modeling/computational science work is still dominated by sets of ODEs, admittedly sometimes fairly elaborate sets of them. One of the plusses of these models is that they're rather easy to describe an...
I have an application that can be trivially parallelized but its performance is to a large extent I/O bound. The application reads a single input array stored in a file that is typically 2-5 GB in size (but I expect this number to grow in the future). A typical computation applies the same operation to each row or colu...
Your situation is a common one in high-performance computing where I/O becomes a bottleneck. Let's explore the options you've mentioned and some additional strategies that could help: ### 1. **Parallel HDF5** Parallel HDF5 is indeed a promising option for your application. It allows multiple processes to read from and...
[ { "from": "human", "value": "I have an application that can be trivially parallelized but its performance is to a large extent I/O bound. The application reads a single input array stored in a file that is typically 2-5 GB in size (but I expect this number to grow in the future). A typical computation appli...
Our workgroup produces a desktop application that simulates building energy performance. It is a .NET application and when the user is running a lot of simulations, they can be quite time consuming. The simulations are totally parallelizable, and we have some very significant HPC computing resources at "the office". O...
Your idea of offloading simulations to HPC resources is a great way to enhance the performance of your desktop application, especially for users running a large number of simulations. Here are some considerations, libraries, and frameworks you could explore to facilitate this process: ### 1. **Message Queuing and Job ...
[ { "from": "human", "value": "Our workgroup produces a desktop application that simulates building energy performance. It is a .NET application and when the user is running a lot of simulations, they can be quite time consuming. The simulations are totally parallelizable, and we have some very significant HP...
I am annotating protein-coding genes in a region of the human genome and am looking for a set of assembled ESTs I can use as evidence for constructing gene models. A quick search of NCBI's SRA shows 4,318 human RNA-seq data sets, so I understand there is no shortage of data. I am hoping, however, to save the time that ...
Yes, there are several resources where you can find assembled ESTs and transcriptome data for Homo sapiens that are not tissue-specific. Here are some notable options: 1. **UniGene**: Although UniGene has been archived, it provided a collection of unique gene-oriented clusters of EST sequences that were useful for gen...
[ { "from": "human", "value": "I am annotating protein-coding genes in a region of the human genome and am looking for a set of assembled ESTs I can use as evidence for constructing gene models. A quick search of NCBI's SRA shows 4,318 human RNA-seq data sets, so I understand there is no shortage of data. I a...
I am used to thinking of finite-differences as a special case of finite-elements, on a very constrained grid. So what are the conditions on how to choose between Finite Difference Method (FDM) and Finite Element Method (FEM) as a numerical method? On the side of Finite Difference Method (FDM), one may count that they a...
When deciding between the Finite Difference Method (FDM) and the Finite Element Method (FEM) for numerical simulations, several factors should be considered, including the problem characteristics, implementation complexity, computational efficiency, and desired accuracy. Here are some guidelines to help make this choic...
[ { "from": "human", "value": "I am used to thinking of finite-differences as a special case of finite-elements, on a very constrained grid. So what are the conditions on how to choose between Finite Difference Method (FDM) and Finite Element Method (FEM) as a numerical method?\nOn the side of Finite Differen...
Our plasma dynamics simulations often produce too much information. During the simulations we record various physical properties on a grid (x,y,z,t) that is as large as (8192x1024x1024x1500), for at least 10 properties. This information is processed after the simulation is completed. With it we make movies of properti...
Maximizing the efficiency of data processing in plasma dynamics simulations (or similar computational simulations) involves several strategies, focusing on data reduction, on-the-fly analysis, and optimal I/O practices. Here are some strategies and insights to consider: ### Strategies for Efficient Data Processing 1....
[ { "from": "human", "value": "Our plasma dynamics simulations often produce too much information. During the simulations we record various physical properties on a grid (x,y,z,t) that is as large as (8192x1024x1024x1500), for at least 10 properties. This information is processed after the simulation is compl...
Specifically I want to extend work involving B3LYP started with Gaussian 03 but continued with GAMESS-US. The energies provided by the default B3LYP methods are not the same. There is a discussion about this in the GAMESS-US manual (Further Information section): Note that B3LYP in GAMESS is based in part on the VWN5 ...
To ensure that your B3LYP calculations are consistent between Gaussian 03 (G03) and GAMESS-US, you need to be aware of the differences in the underlying implementations of the B3LYP functional in these software packages. ### Differences in B3LYP Implementations 1. **VWN Correlation Functional**: As noted in the GAMES...
[ { "from": "human", "value": "Specifically I want to extend work involving B3LYP started with Gaussian 03 but continued with GAMESS-US. The energies provided by the default B3LYP methods are not the same. There is a discussion about this in the GAMESS-US manual (Further Information section):\n\nNote that B3L...
Given two computational programs, one using a Gaussian basis, and the other using Slater basis, what are the practical differences, advantages and disadvantages for each choice ?
When it comes to quantum chemistry calculations, the choice of basis set can significantly affect both the accuracy and the computational efficiency of the results. Two common types of basis sets are Gaussian-type orbitals (GTOs) and Slater-type orbitals (STOs). Here's a comparison of their practical differences, advan...
[ { "from": "human", "value": "Given two computational programs, one using a Gaussian basis, and the other using Slater basis, what are the practical differences, advantages and disadvantages for each choice ? \n" }, { "from": "gpt", "value": "When it comes to quantum chemistry calculations, the c...
I would like to write my own solver for compressible Euler equations, and most importantly I want it to work robustly in all situations. I would like it to be FE based (DG is ok). What are the possible methods? I am aware of doing 0th order DG (finite volumes) and that should work very robustly. I have implemented a ba...
Developing a robust finite element (FE) or discontinuous Galerkin (DG) solver for the compressible Euler equations can be a challenging task, particularly due to issues like shock capturing, spurious oscillations, and stability. Here are some approaches and considerations you might take into account when designing your...
[ { "from": "human", "value": "I would like to write my own solver for compressible Euler equations, and most importantly I want it to work robustly in all situations. I would like it to be FE based (DG is ok). What are the possible methods?\nI am aware of doing 0th order DG (finite volumes) and that should w...
What is the best (scalability and efficiency) algorithms for generating unstructured quad meshes in 2D? Where can I find a good unstructured quad mesh-generator? (open-source preferred)
Generating unstructured quad meshes in 2D can be quite challenging, as it requires careful consideration of factors such as scalability, efficiency, quality of the mesh, and specific application requirements. Here are some of the best algorithms and approaches used for generating unstructured quad meshes, along with so...
[ { "from": "human", "value": "What is the best (scalability and efficiency) algorithms for generating unstructured quad meshes in 2D? \nWhere can I find a good unstructured quad mesh-generator? (open-source preferred)\n" }, { "from": "gpt", "value": "Generating unstructured quad meshes in 2D can ...
Does there exist a standard format for finite element meshes which is widely used in the industry? Thanks!
Yes, there are several standard formats for finite element meshes that are widely used in the industry. Some of the most common formats include: 1. **Nastran (.bdf, .dat)**: The NASA Structural Analysis (Nastran) format is widely used in aerospace and automotive industries for finite element analysis (FEA). It support...
[ { "from": "human", "value": "Does there exist a standard format for finite element meshes which is widely used in the industry?\nThanks!\n" }, { "from": "gpt", "value": "Yes, there are several standard formats for finite element meshes that are widely used in the industry. Some of the most commo...
I can find the random('normal', 0, 1, 10000,1) command in MATLAB but it generates half-normal variates. I would like to generate random half-normal variates. The half-normal distribution is defined by $$f_{|Z|}(x)=\frac{2}{\sqrt{2\pi}}e^\frac{-x^{2}}{2}.$$ Can I generate a random half-normal variates from random norm...
Yes, you can generate random half-normal variates from random normal variates. The half-normal distribution is derived from the normal distribution by taking the absolute value of a normally distributed variable. Here's how you can do it in MATLAB: 1. Generate random samples from a standard normal distribution using ...
[ { "from": "human", "value": "I can find the\nrandom('normal', 0, 1, 10000,1)\n\ncommand in MATLAB but it generates half-normal variates. I would like to generate random half-normal variates. The half-normal distribution is defined by \n$$f_{|Z|}(x)=\\frac{2}{\\sqrt{2\\pi}}e^\\frac{-x^{2}}{2}.$$\nCan I gener...
I'm new to molecular dynamics (MD) simulations. What is the complexity of a molecular dynamics simulation in terms of simulation time? In other words, if I want increase the simulated time from 10 nanoseconds to 20 nanoseconds, what can I expect in terms of the increase in runtime?
The complexity and runtime of molecular dynamics (MD) simulations can be influenced by several factors, including the type of simulation, the size of the system, the choice of integration algorithm, and the use of parallel processing. However, in general, the complexity of MD simulations is often linear with respect to...
[ { "from": "human", "value": "I'm new to molecular dynamics (MD) simulations. What is the complexity of a molecular dynamics simulation in terms of simulation time? In other words, if I want increase the simulated time from 10 nanoseconds to 20 nanoseconds, what can I expect in terms of the increase in runti...
I am trying to fit some raw data using a function of the form $f(r) = \sum_{i=1}^{K} d_kS_k(n_k,\alpha_k,r)$ where $S_k(n_k,\alpha_k,r) = \frac{\alpha_k ^{n_k+3}}{(n_k+2)!}r^{n_k}\exp(-\alpha_kr)$ (note that the actual fit function is far more complex). Now, for each $k$, this has two non-linear parameters ($\alpha_k$ ...
When dealing with a fitting function that has both linear and non-linear parameters, you have several strategies available to you. The choice of method will depend on the complexity of your function, the behavior of your data, and the computational resources you have available. Here are some options you might consider:...
[ { "from": "human", "value": "I am trying to fit some raw data using a function of the form\n$f(r) = \\sum_{i=1}^{K} d_kS_k(n_k,\\alpha_k,r)$\nwhere\n$S_k(n_k,\\alpha_k,r) = \\frac{\\alpha_k ^{n_k+3}}{(n_k+2)!}r^{n_k}\\exp(-\\alpha_kr)$\n(note that the actual fit function is far more complex).\nNow, for each...
I want to study the methods of analyzing textured images. So i searched google scholor but only found very old papers statistical and structural approaches to texture 1979 haralick Image Texture Analysis Techniques - A Survey (1980) Texture analysis — a survey July 1980 Texture Analysis Methods – A Review 1998 Does ...
Yes, there have been numerous advancements in the field of texture analysis since those early surveys. Here are some more recent survey papers that should provide you with updated insights and methodologies: 1. **"A Survey of Image Texture Analysis"** by Song, Y. et al. (2017) - This paper provides a contemporary over...
[ { "from": "human", "value": "I want to study the methods of analyzing textured images. So i searched google scholor but only found very old papers\n\nstatistical and structural approaches to texture 1979 haralick\nImage Texture Analysis Techniques - A Survey (1980)\nTexture analysis — a survey July 1980\nT...
How do I pick a basis set for an ab-initio Hartree-Fock evaluation ? In other words, what are the important characteristics of a basis set so that a proper choice can be made ?
Choosing an appropriate basis set for an ab initio Hartree-Fock calculation is a crucial step in computational quantum chemistry. The basis set you select can significantly influence the accuracy and efficiency of your results. Here are important characteristics and factors to consider when picking a basis set: ### 1....
[ { "from": "human", "value": "How do I pick a basis set for an ab-initio Hartree-Fock evaluation ? In other words, what are the important characteristics of a basis set so that a proper choice can be made ?\n" }, { "from": "gpt", "value": "Choosing an appropriate basis set for an ab initio Hartre...
Sparse linear systems turn up with increasing frequency in applications. One has a lot of routines to choose from for solving these systems. At the highest level, there is a watershed between direct (e.g. sparse Gaussian elimination or Cholesky decomposition, with special ordering algorithms, and multifrontal methods) ...
Choosing between direct and iterative methods for solving sparse linear systems and selecting a particular algorithm involves considering several factors related to the characteristics of the problem and the computational environment. Below are key considerations that can guide your decision-making process: ### 1. Siz...
[ { "from": "human", "value": "Sparse linear systems turn up with increasing frequency in applications. One has a lot of routines to choose from for solving these systems. At the highest level, there is a watershed between direct (e.g. sparse Gaussian elimination or Cholesky decomposition, with special orderi...
In both domain decomposition (DD) and multigrid (MG) methods, one may compose the application of the block updates or coarse corrections as either additive or multiplicative. For pointwise solvers, this is the difference between the Jacobi and Gauss-Seidel iterations. The multiplicative smoother for $Ax = b$ acting as ...
The choice between additive and multiplicative smoothers can significantly impact the convergence properties of iterative solvers, and while multiplicative smoothers (like Gauss-Seidel) often exhibit faster convergence, there are specific scenarios where additive smoothers (like Jacobi) can outperform their multiplicat...
[ { "from": "human", "value": "In both domain decomposition (DD) and multigrid (MG) methods, one may compose the application of the block updates or coarse corrections as either additive or multiplicative. For pointwise solvers, this is the difference between the Jacobi and Gauss-Seidel iterations. The multip...
I have several challenging non-convex global optimization problems to solve. Currently I use MATLAB's Optimization Toolbox (specifically, fmincon() with algorithm='sqp'), which is quite effective. However, most of my code is in Python, and I'd love to do the optimization in Python as well. Is there a NLP solver with...
Given your requirements for a robust NLP solver with Python bindings that can handle nonlinear equality and inequality constraints without the need for user-provided Jacobians, you might want to consider the following options: 1. **SciPy's `optimize.minimize` with `method='trust-constr'`:** - SciPy is a widely-used...
[ { "from": "human", "value": "I have several challenging non-convex global optimization problems to solve. Currently I use MATLAB's Optimization Toolbox (specifically, fmincon() with algorithm='sqp'), which is quite effective. However, most of my code is in Python, and I'd love to do the optimization in Py...
I solve a lot of PDEs numerically, but applied math isn't my field. I haven't picked up on which applied math journals I should read to keep up with recent developments in the field. What are good journals to read to keep up with recent developments in solving PDEs numerically?
If you're interested in keeping up with recent developments in the numerical solution of partial differential equations (PDEs), here are some reputable journals that frequently publish relevant research: 1. **Journal of Computational Physics** - This journal focuses on numerical methods and computational techniques in...
[ { "from": "human", "value": "I solve a lot of PDEs numerically, but applied math isn't my field. I haven't picked up on which applied math journals I should read to keep up with recent developments in the field.\nWhat are good journals to read to keep up with recent developments in solving PDEs numerically?...
Whenever one uses a quasi-Monte Carlo method for cubature or optimization, it seems that there's a wide variety of low-discrepancy sequences to choose from, associated with the names of van der Corput, Halton, Hammersley, Faure, Niederreiter, Sobol', and other names I don't quite remember. Are there any good rules of t...
Choosing the right low-discrepancy sequence (LDS) for quasi-Monte Carlo methods depends on various factors, including the dimensionality of the problem, the smoothness of the integrand or objective function, and the specific requirements of the computation. Here are some rules of thumb and considerations to help guide ...
[ { "from": "human", "value": "Whenever one uses a quasi-Monte Carlo method for cubature or optimization, it seems that there's a wide variety of low-discrepancy sequences to choose from, associated with the names of van der Corput, Halton, Hammersley, Faure, Niederreiter, Sobol', and other names I don't quit...
Fortran has a special place in numerical programming. You can certainly make good and fast software in other languages, but Fortran keeps performing very well despite its age. Moreover, it's easier to make fast programs in Fortran. I've made fast programs in C++, but you have to be more careful about things like pointe...
You raise some important points regarding Fortran’s strengths in numerical programming. Indeed, Fortran's design and its characteristics make it particularly well-suited for high-performance scientific computing. Here are some technical details that highlight why Fortran can achieve high performance, and how you might ...
[ { "from": "human", "value": "Fortran has a special place in numerical programming. You can certainly make good and fast software in other languages, but Fortran keeps performing very well despite its age. Moreover, it's easier to make fast programs in Fortran. I've made fast programs in C++, but you have to...
I am trying to put together a complete list of all of the tools that computational scientists have found useful when trying to munge data, i.e. take data in one format, extract the useful bits, and put it into a different format. So what are the libraries that you've used in the past to obtain data from fixed-width, CS...
Certainly! Data munging, also known as data wrangling or data preprocessing, is a critical step in computational science and data analysis. Here’s a comprehensive list of libraries and tools that computational scientists commonly use for data manipulation, extraction, and transformation across various formats: ### Pyt...
[ { "from": "human", "value": "I am trying to put together a complete list of all of the tools that computational scientists have found useful when trying to munge data, i.e. take data in one format, extract the useful bits, and put it into a different format.\nSo what are the libraries that you've used in th...
What is a good, common way to express dictionaries (= maps) in pseudocode? I.e. datastructures that basically allow to store values for keys, iterate over all key/value pairs, test for inclusion of a given key, etc. I have something like the following (in this case senseless) Python code in mind: D = {} D[1] = 2 for ke...
When writing pseudocode for dictionaries (or maps) in a publication, clarity and readability are key. It's important to strike a balance between mathematical rigor and programming conventions so that your pseudocode is understandable to a broad audience, including those familiar with programming as well as those with a...
[ { "from": "human", "value": "What is a good, common way to express dictionaries (= maps) in pseudocode? I.e. datastructures that basically allow to store values for keys, iterate over all key/value pairs, test for inclusion of a given key, etc. I have something like the following (in this case senseless) Py...
You've managed to finally find out how the atoms are spatially arranged on your newly-discovered molecular entity. Through, say, spectroscopic means, you are now in possession of a bunch of atom coordinates, atom types, bond lengths, bond types, and whatnot for your molecule. You are now interested in determining the p...
Determining the point group of a molecule algorithmically involves several steps, largely focused on analyzing its symmetry elements. Here’s a step-by-step approach you can use: ### 1. Data Preparation - **Read Molecular Structure Data**: Import the molecular coordinates, atom types, and bonding information from the p...
[ { "from": "human", "value": "You've managed to finally find out how the atoms are spatially arranged on your newly-discovered molecular entity. Through, say, spectroscopic means, you are now in possession of a bunch of atom coordinates, atom types, bond lengths, bond types, and whatnot for your molecule. Yo...
I have a PETSc Mat and would like to estimate its condition number.
To estimate the condition number of a matrix in PETSc, you typically use the `MatCreate()` function to create the matrix and then utilize the `KSP` (Krylov Subspace Methods) solver to estimate the condition number. The condition number can be estimated using the matrix's norms (specifically, the 2-norm) or by using the...
[ { "from": "human", "value": "I have a PETSc Mat and would like to estimate its condition number.\n" }, { "from": "gpt", "value": "To estimate the condition number of a matrix in PETSc, you typically use the `MatCreate()` function to create the matrix and then utilize the `KSP` (Krylov Subspace M...
This is mostly aimed for elliptic PDEs over convex domains, so that I can get a good overview of the two methods.
Certainly! When tackling elliptic partial differential equations (PDEs) over convex domains, two prominent methods often discussed are the **variational method** (or weak formulation method) and the **finite element method (FEM)**. Below is an overview of both approaches, highlighting their key concepts, advantages, an...
[ { "from": "human", "value": "This is mostly aimed for elliptic PDEs over convex domains, so that I can get a good overview of the two methods.\n" }, { "from": "gpt", "value": "Certainly! When tackling elliptic partial differential equations (PDEs) over convex domains, two prominent methods often...
A lot of numerical algorithms (integration, differentiation, interpolation, special functions, etc.) are available in scientific computation libraries like GSL. But I often see code with "hand-rolled" implementations of these functions. For small programs which are not necessarily intended for public distribution, is i...
In scientific computing, especially within the C and C++ ecosystems, you will find a mix of practices regarding the implementation of numerical algorithms. While it is generally recommended to leverage existing libraries like GSL (GNU Scientific Library), the prevalence of "hand-rolled" implementations can be attribute...
[ { "from": "human", "value": "A lot of numerical algorithms (integration, differentiation, interpolation, special functions, etc.) are available in scientific computation libraries like GSL. But I often see code with \"hand-rolled\" implementations of these functions. For small programs which are not necessa...
Given an evolution PDE $$u_t = Au + Bu$$ where $A,B$ are (possibly nonlinear) differential operators that don't commute, a common numerical approach is to alternate between solving $$u_t = Au$$ and $$u_t = Bu.$$ The simplest implementation of this is known as Godunov splitting and is 1st-order accurate. Another well-k...
Yes, higher-order operator splitting methods do exist, and they are indeed valuable when dealing with evolution PDEs of the form \( u_t = Au + Bu \) where \( A \) and \( B \) are differential operators that do not commute. ### Higher-Order Splitting Methods 1. **Strang Splitting**: As you noted, the Strang splitting...
[ { "from": "human", "value": "Given an evolution PDE\n$$u_t = Au + Bu$$\nwhere $A,B$ are (possibly nonlinear) differential operators that don't commute, a common numerical approach is to alternate between solving\n$$u_t = Au$$\nand\n$$u_t = Bu.$$\nThe simplest implementation of this is known as Godunov split...
I would like to test the influence of solvation parameters in implicit solvation models and wonder which codes are freely available as standalone programs for protein folding of small proteins, and which use energy minimization approaches instead of dynamics, so I am not looking for molecular dynamics codes.
There are several freely available standalone software packages that focus on energy minimization and can incorporate implicit solvation models for small proteins. Here are some noteworthy options: 1. **AMBER**: - While primarily known for molecular dynamics, AMBER includes tools for energy minimization using impli...
[ { "from": "human", "value": "I would like to test the influence of solvation parameters in implicit solvation models and wonder which codes are freely available as standalone programs for protein folding of small proteins, and which use energy minimization approaches instead of dynamics, so I am not looking...
I'm trying to create a figure of particle distribution from a reference surface in python. I plan to get a distribution in python and then prettify it with tikz. I tried this: xs = np.linspace(-1, 1, 10) ys = np.linspace(-1, 1, 10) X, Y = np.meshgrid(xs, ys) Z = X for i in range (0, 10): for j in range (0, 10): ...
The issue you're encountering stems from how you are generating your surface and how you're using it in the `plot_surface` method. To create a reference surface and visualize a 3D scatter plot, follow these steps: 1. Create a meshgrid for `X` and `Y` coordinates. 2. Define `Z` values for the reference surface (which c...
[ { "from": "human", "value": "I'm trying to create a figure of particle distribution from a reference surface in python. I plan to get a distribution in python and then prettify it with tikz. I tried this:\nxs = np.linspace(-1, 1, 10)\nys = np.linspace(-1, 1, 10)\nX, Y = np.meshgrid(xs, ys)\n\nZ = X\nfor i i...
Recently, I've encountered a bizarre problem with FORTRAN95. I initialized variables X and Y as follows: X=1.0 Y=0.1 Later I add them together and print the result: 1.10000000149012 After examining the variables, it seems as though 0.1 is not represented in double precision with full accuracy. Is there any way t...
The issue you're encountering with floating-point representation is a common one in computing, particularly in languages like FORTRAN (and many others) that use binary floating-point arithmetic. The value 0.1 cannot be exactly represented in binary floating-point, which leads to small errors in calculations. In your ...
[ { "from": "human", "value": "Recently, I've encountered a bizarre problem with FORTRAN95. I initialized variables X and Y as follows: \nX=1.0\nY=0.1\n\nLater I add them together and print the result: \n1.10000000149012\n\nAfter examining the variables, it seems as though 0.1 is not represented in double p...
I have a Mathematica program which performs some integrals in 3 or 4 dimensions using the QuasiMonteCarlo method. The problem is, it takes an annoyingly long time to run, to the point where some of these calculations can't complete in the maximum job time available on our HPC cluster. So I'm considering rewriting the p...
If you're looking to implement Quasi-Monte Carlo (QMC) integration in C++, there are a few options and libraries you can consider. While the GNU Scientific Library (GSL) provides utilities for random sequences and MC integration, it doesn’t specifically include high-level implementations for QMC integration directly. I...
[ { "from": "human", "value": "I have a Mathematica program which performs some integrals in 3 or 4 dimensions using the QuasiMonteCarlo method. The problem is, it takes an annoyingly long time to run, to the point where some of these calculations can't complete in the maximum job time available on our HPC cl...
Are there any existing software toolkits, libraries, frameworks or whatever for studying the quality of pseudorandom number generators that allow one to add a known amount of imperfection - e.g deliberate higher-order correlations - then obtain statistics of various RNGs whose outputs are so modified?
Yes, there are several software toolkits, libraries, and frameworks that can be used for studying the quality of pseudorandom number generators (PRNGs) and for conducting statistical analysis on their outputs. Below are some tools and libraries that might meet your needs, including the ability to manipulate the randomn...
[ { "from": "human", "value": "Are there any existing software toolkits, libraries, frameworks or whatever for studying the quality of pseudorandom number generators that allow one to add a known amount of imperfection - e.g deliberate higher-order correlations - then obtain statistics of various RNGs whose o...
Peersim is a peer-to-peer network simulator. I'm simply trying to get the program to print out the network (an edge list is fine). Presumably this is possible, since there is an in-built writeEdgeList function. I suspect there is an easy way to do this by modifying this line in the example: include.control io degree ...
To print out an edge list of a network in Peersim, you can use the built-in functionality to write the edge list directly. Here's how you can modify the control parameters in your simulation configuration to achieve this. In your Peersim configuration file, instead of using `include.control io degree`, you'll want to ...
[ { "from": "human", "value": "Peersim is a peer-to-peer network simulator. I'm simply trying to get the program to print out the network (an edge list is fine). Presumably this is possible, since there is an in-built writeEdgeList function.\nI suspect there is an easy way to do this by modifying this line ...
After configuring and building PETSc, I have successfully been able to run several examples. In particular, I am working with this example. I have been able to run the program using the following commands: make ex2 mpiexec -n 4 ./ex2 -m 40 -n 40 which produces the following output: Norm of error 0.000642883 ite...
It sounds like you're encountering an issue where your PETSc example is not utilizing multiple processors as expected, and it's running the same computation independently on each processor. There are a few things you can check to troubleshoot and resolve the issue: 1. **Code Structure**: Ensure that the `ex2` example ...
[ { "from": "human", "value": "After configuring and building PETSc, I have successfully been able to run several examples. In particular, I am working with this example. I have been able to run the program using the following commands: \nmake ex2\nmpiexec -n 4 ./ex2 -m 40 -n 40 \nwhich produces the follo...
As I understand it, since a solution to a linear program always occurs at a vertex of its polyhedral feasible set (if a solution exists and the optimal objective function value is bounded from below, assuming a minimization problem), how can a search through the interior of the feasible region be better? Does it conve...
You are correct that a solution to a linear program (LP) occurs at a vertex of the feasible set, but the efficiency and practicality of solving LPs can vary depending on the method used. Let's break down your questions regarding the comparison between the simplex method and interior point methods. ### 1. Search throug...
[ { "from": "human", "value": "As I understand it, since a solution to a linear program always occurs at a vertex of its polyhedral feasible set (if a solution exists and the optimal objective function value is bounded from below, assuming a minimization problem), how can a search through the interior of the ...
I have heard that one of the current goals in scientific computing is to surpass the exascale level by 2018 or so... After having passed the petascale a few years ago, one would think that the exascale wouldn't be so much of a challenge... If it's theoretically possible, what challenges are there to computing at this s...
Exascale computing refers to systems capable of performing at least \(10^{18}\) calculations per second, or one exaflop. The goal of reaching exascale performance has been a significant focus in the scientific computing community, particularly in the United States and several other countries. While it may seem that mo...
[ { "from": "human", "value": "I have heard that one of the current goals in scientific computing is to surpass the exascale level by 2018 or so... After having passed the petascale a few years ago, one would think that the exascale wouldn't be so much of a challenge... If it's theoretically possible, what ch...
My question is related in spirit to "Is algorithmic analysis by flop counting obsolete?". Counting the number of computational operations in an algorithm is commonly used as a first-order model to aid in understanding the computational costs of an algorithm. However, the unit cost (in, say, time per operation) of data...
The analysis of communication costs, much like flop counting for computational operations, has gained increased attention in the context of modern computing systems, particularly with the rise of parallel computing, distributed systems, and large-scale data processing. While there isn't a universally adopted method equ...
[ { "from": "human", "value": "My question is related in spirit to \"Is algorithmic analysis by flop counting obsolete?\". Counting the number of computational operations in an algorithm is commonly used as a first-order model to aid in understanding the computational costs of an algorithm. However, the unit...
Multi-physics simulation involves coupling multiple "physics", often with different space and/or time scales. Additionally, the single-physics codes are often written by different teams. The most commonly used coupling technique is first-order operator splitting, but this has poor accuracy and stability properties. How...
Determining effective algorithms for multi-physics simulation, especially in the context of different space and time scales, involves a careful analysis of your specific problem, the characteristics of the physics involved, and the interactions between those physical phenomena. Here are the steps you can take to select...
[ { "from": "human", "value": "Multi-physics simulation involves coupling multiple \"physics\", often with different space and/or time scales. Additionally, the single-physics codes are often written by different teams. The most commonly used coupling technique is first-order operator splitting, but this has ...
I have created a spline to fit my data in python using: spline=scipy.interpolate.UnivariateSpline(energy, fpp, k=4) The equation I want to use involves a summation between n=2 and n=infinity, where n is the order of the differential at a point Eo. However, using; UnivariateSpline.__call__(spline, e0, nu=n) to call in...
The `scipy.interpolate.UnivariateSpline` class is designed for fitting a spline to your data, but it only directly supports derivatives up to the degree of the spline itself (in your case, a 4th degree spline). If you need to compute higher-order derivatives beyond the spline's order, you'll need to use a different app...
[ { "from": "human", "value": "I have created a spline to fit my data in python using:\nspline=scipy.interpolate.UnivariateSpline(energy, fpp, k=4)\n\nThe equation I want to use involves a summation between n=2 and n=infinity, where n is the order of the differential at a point Eo. However, using;\nUnivariate...
Considering regular matrix approximation inequality || $A - QQ^TA $|| < e where we try to approximate matrix $A$ by a lower rank orthonormal matrix $Q$. I've read an article on probabilistic algorithms for such an purpose. You simply pick random (Gaussian etc.) vectors $\omega$, then generate vectors from the range of ...
Your problem relates to matrix approximation, low-rank representations, and how to generalize these representations to new, partially observed data. Given your two-phase approach, there are several areas in machine learning and numerical linear algebra that could provide useful insights and references. ### References ...
[ { "from": "human", "value": "Considering regular matrix approximation inequality\n|| $A - QQ^TA $|| < e\nwhere we try to approximate matrix $A$ by a lower rank orthonormal matrix $Q$. I've read an article on probabilistic algorithms for such an purpose. You simply pick random (Gaussian etc.) vectors $\\omeg...
When I run a PETSc example in parallel with the flag "-log_summary", the first two tables of information look something like this: Max Max/Min Avg Total Time (sec): 2.512e-01 1.00547 2.505e-01 Objects: 5.800e+01 1.00000 5.800e+01 Flops: ...
When using the `-log_summary` option in PETSc, you receive a detailed breakdown of various performance metrics for your parallel execution. To determine the "overall execution time," you should focus on the "Max Time" value in the first table, which represents the maximum execution time across all processes. This time ...
[ { "from": "human", "value": "When I run a PETSc example in parallel with the flag \"-log_summary\", the first two tables of information look something like this: \n Max Max/Min Avg Total \nTime (sec): 2.512e-01 1.00547 2.505e-01\nObjects: ...
Usually one would consult a paper or book to find integration points and weights for unit triangle and tetrahedra. I am looking for a method to automatically compute such points and weights. The following Mathematica code example computes integration weights and points for unit line (quad/hexahedron) elements: unitGau...
Certainly! The computation of Gaussian quadrature points and weights for triangles and tetrahedra is a well-studied topic in numerical integration, especially in the context of finite element analysis. Here are some references and resources that describe algorithms for obtaining these points and weights: 1. **Books**:...
[ { "from": "human", "value": "Usually one would consult a paper or book to find integration points and weights for unit triangle and tetrahedra. I am looking for a method to automatically compute such points and weights. The following Mathematica code example computes integration weights and points for unit...
I'm playing with simple implementations of algorithms to find minimum vertex cover/maximum cardinality matching in bipartite graphs. However, I seem to have trouble googling for some test data sets that I could use to verify, if I got that one right. It's easy to devise simple examples that one could check on paper, bu...
There are several sources and datasets that can be useful for testing and benchmarking algorithms related to vertex cover and maximum matching in bipartite graphs. Here are some recommendations: ### 1. **Standard Graph Libraries** - **DIMACS Challenge:** The DIMACS (Center for Discrete Mathematics and Theoretical C...
[ { "from": "human", "value": "I'm playing with simple implementations of algorithms to find minimum vertex cover/maximum cardinality matching in bipartite graphs. However, I seem to have trouble googling for some test data sets that I could use to verify, if I got that one right.\nIt's easy to devise simple ...
I'm using the Crank-Nicholson method to solve the time-dependent Schrödinger equation with the split-operator method. I'm getting some weird results that are probably the result of a bug somewhere in my code. Just in case, I thought I should probably check to see if the method I'm using is unstable. Does the split-oper...
The Crank-Nicholson method is an implicit numerical scheme used for solving partial differential equations, including the time-dependent Schrödinger equation. It is known for being unconditionally stable and providing second-order accuracy in both time and space. The split-operator method, when applied to the Crank-N...
[ { "from": "human", "value": "I'm using the Crank-Nicholson method to solve the time-dependent Schrödinger equation with the split-operator method. I'm getting some weird results that are probably the result of a bug somewhere in my code.\nJust in case, I thought I should probably check to see if the method ...
I have a fortran 90 code that distributes blocks of computations (from a matrix) to multiple nodes in a cluster using MPI, but in each node, the for loops are executed in parallel using openmp. I tried using the following command: mpif90 mycode.f which produces the following output: mycode.f(49): (col. 3) remark: LOO...
The error you're encountering indicates that the OpenMP runtime library isn't being linked correctly when you compile your Fortran code using MPI. The `omp_set_num_threads_` function is part of the OpenMP library, and the undefined reference error means that the linker cannot find the implementation of this function. ...
[ { "from": "human", "value": "I have a fortran 90 code that distributes blocks of computations (from a matrix) to multiple nodes in a cluster using MPI, but in each node, the for loops are executed in parallel using openmp. I tried using the following command:\nmpif90 mycode.f\n\nwhich produces the followin...
According to these lecture notes, a checkerboard block decomposition should exhibit better scalability when applied to parallel matrix-vector multiplication (presumably because of greater cache hit rate). Since the conjugate gradient method also uses a matrix-vector multiplication, I would think that this form of bloc...
Yes, there are indeed some advantages to using row or column striped block decomposition over checkerboard block decomposition in the context of parallel implementations of the conjugate gradient method and similar algorithms, despite the theoretical benefits of checkerboard decomposition in terms of cache locality. #...
[ { "from": "human", "value": "According to these lecture notes, a checkerboard block decomposition should exhibit better scalability when applied to parallel matrix-vector multiplication (presumably because of greater cache hit rate). Since the conjugate gradient method also uses a matrix-vector multiplicat...
Every scientist needs to know a bit about statistics: what correlation means, what a confidence interval is, and so on. Similarly, every scientist ought to know a bit about computing: the question is, what? What it is reasonable to expect every working scientist to know about building and using software? Our list of co...
Your list of core skills is a solid foundation for any working scientist in today’s data-driven research landscape. To refine it and ensure it aligns with the current demands of scientific work, I would consider the following additions and adjustments: ### Recommended Core Skills for Every Scientist 1. **Basic Progra...
[ { "from": "human", "value": "Every scientist needs to know a bit about statistics: what correlation means, what a confidence interval is, and so on. Similarly, every scientist ought to know a bit about computing: the question is, what? What it is reasonable to expect every working scientist to know about bu...
Are there any good papers and or codes that couple discontinuous galerkin finite element solvers with Riemann solvers? I need to explore coupling elliptic and hyperbolic problems but most splitting methods are ad hoc at best. Since I have a large amount of FEniCS code, I would like to just couple the Riemann solver ...
Coupling discontinuous Galerkin (DG) finite element methods with Riemann solvers is indeed a powerful approach, especially for handling problems that involve both hyperbolic and elliptic characteristics. Here are some resources that you may find useful in your exploration of this subject: ### Papers 1. **"Discontinuou...
[ { "from": "human", "value": "Are there any good papers and or codes that couple discontinuous galerkin finite element solvers with Riemann solvers? \nI need to explore coupling elliptic and hyperbolic problems but most splitting methods are ad hoc at best. Since I have a large amount of FEniCS code, I wou...
The title says most of it. I'm looking for a lightweight and easy-to-use library that I can use for Android (NDK) projects. For dense stuff I like using Eigen but I haven't found many comprehensive (and documented!) libraries for sparse stuff that "just work" in a project. PETSc seems a little heavy with all these MPI ...
For working with sparse matrices in Android (NDK) projects, you have several options for lightweight and easy-to-use libraries. Here are a few suggestions that you might find helpful: 1. **Eigen** (Sparse Module): - Although you mentioned that you typically use Eigen for dense matrices, it also has robust support f...
[ { "from": "human", "value": "The title says most of it.\nI'm looking for a lightweight and easy-to-use library that I can use for Android (NDK) projects.\nFor dense stuff I like using Eigen but I haven't found many comprehensive (and documented!) libraries for sparse stuff that \"just work\" in a project.\n...
Suppose one is performing Gibbs sampling with a Boltzmann distribution (or if you prefer, simulated annealing) at finite temperature. In general we would want to anneal: as the sampler converges to equilibrium, the temperature should be decreased. If the sampler's rate of convergence (local in time) does not vary, the...
The concept you've mentioned about dynamically adjusting the temperature based on the convergence rate in Gibbs sampling or simulated annealing is indeed an interesting one, and there are several related ideas in the literature. 1. **Adaptive Simulated Annealing**: This is a well-known approach where the temperature s...
[ { "from": "human", "value": "Suppose one is performing Gibbs sampling with a Boltzmann distribution (or if you prefer, simulated annealing) at finite temperature. In general we would want to anneal: as the sampler converges to equilibrium, the temperature should be decreased. \nIf the sampler's rate of conv...
As we know, orthogonal transformations methods (Givens rotations and Housholder reflections) for systems of linear equations are more expensive than Gaussian elimination, but theoretically have nicer stability properties in the sense that they do not change the condition number of the system. Although I know just one a...
The question of the stability of different methods for solving systems of linear equations, particularly in relation to Gaussian elimination and orthogonal transformations, is indeed an important area of research in numerical linear algebra. Here are some avenues you might explore to gain deeper insights into this topi...
[ { "from": "human", "value": "As we know, orthogonal transformations methods (Givens rotations and Housholder reflections) for systems of linear equations are more expensive than Gaussian elimination, but theoretically have nicer stability properties in the sense that they do not change the condition number ...
I'm trying to solve a 2D Poisson equation by finite differences. In the process, I obtain a sparse matrix with only $5$ variables in each equation. For example, if the variables were $U$, then the discretization would yield: $$U_{i-1,j} + U_{i+1,j} -4U_{i,j} + U_{i,j-1} + U_{i,j+1} = f_{i,j}$$ I know that I can solve ...
Yes, it is indeed possible to rearrange the variables of the system derived from the discretization of a 2D Poisson equation to obtain a banded matrix structure. The general approach you are considering involves indexing the unknown variables in such a way that the resulting matrix maintains sparsity while also being s...
[ { "from": "human", "value": "I'm trying to solve a 2D Poisson equation by finite differences. In the process, I obtain a sparse matrix with only $5$ variables in each equation. For example, if the variables were $U$, then the discretization would yield:\n$$U_{i-1,j} + U_{i+1,j} -4U_{i,j} + U_{i,j-1} + U_{i...
As far as I am aware, multigrid solvers use iterative smoothers such as Jacobi, Gauss-Seidel, and SOR to dampen the error at various frequencies. Could a Krylov subspace method (like conjugate gradient, GMRES, etc.) be utilized instead? I don't think they are classified as "smootheners", but they can be used to appro...
Yes, Krylov subspace methods such as Conjugate Gradient (CG) or Generalized Minimal Residual (GMRES) can indeed be used in multigrid methods as alternatives to traditional smoothers like Jacobi, Gauss-Seidel, or SOR. The idea is to apply a Krylov method as a smoother to reduce high-frequency errors, as traditional smoo...
[ { "from": "human", "value": "As far as I am aware, multigrid solvers use iterative smoothers such as Jacobi, Gauss-Seidel, and SOR to dampen the error at various frequencies. Could a Krylov subspace method (like conjugate gradient, GMRES, etc.) be utilized instead? I don't think they are classified as \"s...
I know that delaunay triangulation can be extended into arbitrary dimensions by solving the convex hull problem in $(p+1)$ dimensions and projecting the lower hull into dimension $p$ to obtain a mesh in dimension $p$. However, this approach is asymptotically $\Omega({n}^{{p}/{2}})$. I was wondering if there are any o...
Delaunay triangulation can indeed be extended to arbitrary dimensions, and while the convex hull approach leads to an asymptotic runtime of \(\Omega(n^{p/2})\), there are other techniques and algorithms that can be employed for faster implementations in higher dimensions. Here are a few notable methods: ### 1. Increme...
[ { "from": "human", "value": "I know that delaunay triangulation can be extended into arbitrary dimensions by solving the convex hull problem in $(p+1)$ dimensions and projecting the lower hull into dimension $p$ to obtain a mesh in dimension $p$. However, this approach is asymptotically $\\Omega({n}^{{p}/{...
I have a linear system of equations of size mxm, where m is large. However, the variables that I'm interested in are just the first n variables (n is small compared to m). Is there a way I can approximate the solution for the first m values without having to solve the entire system? If so, would this approximation b...
Yes, it is possible to approximate the solution for the first \( n \) variables of a large linear system of equations without solving the entire system explicitly. There are several methods to achieve this, and their efficiency can depend on the structure of the matrix and the properties of the system. Here are a few s...
[ { "from": "human", "value": "I have a linear system of equations of size mxm, where m is large. However, the variables that I'm interested in are just the first n variables (n is small compared to m). Is there a way I can approximate the solution for the first m values without having to solve the entire s...
I have a list of vertical cut planes, and I have a polygonal mesh ( it's a 2D+0.5D mesh, something like a 2D mesh with an extra dimension, $z$ attached to each point). One can assume that the mesh contains vertices $V$ , edges $E$ and face $F$. The mesh is a real life 3D terrain. Now, given a list of vertical cut plane...
Your approach of using an AABB tree to cull triangles that intersect with your vertical cut planes is a solid starting point, but as you noted, you can leverage the mesh structure for efficiency. Here are several strategies to optimize your algorithm further: ### 1. **Spatial Partitioning Based on Mesh Structure:** In...
[ { "from": "human", "value": "I have a list of vertical cut planes, and I have a polygonal mesh ( it's a 2D+0.5D mesh, something like a 2D mesh with an extra dimension, $z$ attached to each point). One can assume that the mesh contains vertices $V$ , edges $E$ and face $F$.\nThe mesh is a real life 3D terrai...
It is quite painful to discover that a few-day long job is going to be prematurely killed due to an error in setting walltime limit for it. Is there a way to change it for a running PBS job?
In PBS (Portable Batch System), once a job is submitted with a specific walltime limit, it is generally not possible to change the walltime for that running job directly. The walltime limit is set during the job submission process and is enforced by the PBS scheduler. However, there are a couple of approaches you can ...
[ { "from": "human", "value": "It is quite painful to discover that a few-day long job is going to be prematurely killed due to an error in setting walltime limit for it.\nIs there a way to change it for a running PBS job?\n" }, { "from": "gpt", "value": "In PBS (Portable Batch System), once a job...
I am trying to solve the following test problem which is well-known in the community in different variants: Place N = 15 points in the 3-dim. unit cube such that the minimal distance between them is maximal, e.g. like in the case of repellent but confined electrons. Here are Matlab-like non-vectorized/vectorized forms ...
To tackle the problem of placing 15 points in a 3D unit cube while maximizing the minimum distance between them using open-source methods, we can consider several approaches. Since you want an accurate computation of the minimal value while avoiding local minima issues, stochastic optimization algorithms such as Geneti...
[ { "from": "human", "value": "I am trying to solve the following test problem which is well-known in the community in different variants:\nPlace N = 15 points in the 3-dim. unit cube such that the minimal distance between them is maximal, e.g. like in the case of repellent but confined electrons.\nHere are M...
Consider an IVP for ODE system $y'=f(x,y)$, $y(x_0)=y_0$. Most commonly this problem is considered stiff when Jacobi matrix $\frac{\partial f}{\partial y}(x_0,y_0)$ has both eigenvalues with very large negative real part and eigenvalues with very small negative real part (I consider only the stable case). On the other ...
### Understanding Stiffness in ODE Systems To answer your questions on stiffness in ordinary differential equation (ODE) systems, let's begin by clarifying why we include both small and large negative eigenvalues in the stiffness definition for systems. #### 1. Why Include Small Eigenvalues in the Definition of Stiff...
[ { "from": "human", "value": "Consider an IVP for ODE system $y'=f(x,y)$, $y(x_0)=y_0$. Most commonly this problem is considered stiff when Jacobi matrix $\\frac{\\partial f}{\\partial y}(x_0,y_0)$ has both eigenvalues with very large negative real part and eigenvalues with very small negative real part (I c...
Recently, I've been asking about methods to solve a finite difference discretization of the 2D Poisson equation (see here and here) of the form: $$U_{i-1,j} + U_{i+1,j} -4U_{i,j} + U_{i,j-1} + U_{i,j+1} = f_{i,j}$$ The left hand side of this system is often referred to as the 5-point discrete Laplacian. Suppose that...
Your problem involving the modified discrete Laplacian can indeed be tackled using various numerical methods, particularly given the characteristics of the matrix involved. Here are some thoughts on the approaches you've mentioned and their applicability to your system: 1. **Sparse Direct Solvers**: Since your syst...
[ { "from": "human", "value": "Recently, I've been asking about methods to solve a finite difference discretization of the 2D Poisson equation (see here and here) of the form: \n$$U_{i-1,j} + U_{i+1,j} -4U_{i,j} + U_{i,j-1} + U_{i,j+1} = f_{i,j}$$\nThe left hand side of this system is often referred to as th...
I found the following thread in the physics stackexchange where I saw the video called output attached to the main post. The video can be found here. How would I go about creating such an animation?
Creating an animation similar to the one described in the Stack Exchange thread requires a combination of understanding the concepts being illustrated, selecting the right tools, and executing the animation. Here’s a general step-by-step guide to help you create such an animation: ### 1. **Conceptualize the Animation*...
[ { "from": "human", "value": "I found the following thread in the physics stackexchange where I saw the video called output attached to the main post. The video can be found here.\nHow would I go about creating such an animation?\n" }, { "from": "gpt", "value": "Creating an animation similar to t...
I'm preparing for a thesis in computer science on calculations based on concepts from Neuroelectrodynamics. In short this theory states, that information transfer is not done by spike time coding, but by movement of electric charges. Also this charges affect (and get affected by) proteins in the brain cells, so the cel...
Your thesis topic on Neuroelectrodynamics and the computation of electric charges in neural systems is fascinating and interdisciplinary, bridging concepts in neuroscience, physics, and computer science. Here’s an outline of how electric charges can be represented in programming and some resources to get you started in...
[ { "from": "human", "value": "I'm preparing for a thesis in computer science on calculations based on concepts from Neuroelectrodynamics.\nIn short this theory states, that information transfer is not done by spike time coding, but by movement of electric charges. Also this charges affect (and get affected b...
I'm trying to figure out how to draw a wave equation progress in a 2D graph with Matlab. I found this piece of code which effectively draw a 2D wave placing a droplet in the middle of the graph (I almost fully commented it to simplify things) and then letting it expanding till the border, then bouncing back (how can th...
Let's break down the code you provided for simulating a 2D wave in MATLAB and clarify some of your questions regarding how it works. ### 1. Wave Equation and Code Mechanics The wave equation describes how waves propagate through a medium. In this case, we have a 2D wave equation, which can be represented in a discrete...
[ { "from": "human", "value": "I'm trying to figure out how to draw a wave equation progress in a 2D graph with Matlab.\nI found this piece of code which effectively draw a 2D wave placing a droplet in the middle of the graph (I almost fully commented it to simplify things) and then letting it expanding till ...
In Finite Element theory, and other methods in scientific computing for PDEs, one uses meshes which fulfill several regularity criteria, many of them being equivalent. It is of interest to have notions of shape-regularity in arbitrary dimensions. While some authors use this as if there were full analogies of the two-di...
In the study of finite element methods and mesh quality, shape-regularity is an important concept that extends to arbitrary dimensions. While traditional literature often focuses on two or three dimensions, there are indeed resources that discuss mesh regularity in a more general setting. One seminal reference that di...
[ { "from": "human", "value": "In Finite Element theory, and other methods in scientific computing for PDEs, one uses meshes which fulfill several regularity criteria, many of them being equivalent.\nIt is of interest to have notions of shape-regularity in arbitrary dimensions. While some authors use this as ...
Suppose $$\begin{align*} \min A &\mathrm{vec}(U) \\ &\text{subject to } U_{i,j} \leq \max\{U_{i,k}, U_{k,j}\}, \quad i,j,k = 1, \ldots, n \end{align*}$$ where $U$ is a symmetric $n\times n$ matrix, and $\mathrm{vec}(U)$ reshapes $U$ into a one-dimensional vector with $n^2$ entries. The part of the above program that...
The optimization problem you're working with involves a matrix \( U \) subject to a constraint involving the maximum of elements in \( U \). The constraint is of the form: \[ U_{i,j} \leq \max\{U_{i,k}, U_{k,j}\}, \quad i,j,k = 1, \ldots, n. \] This type of constraint can be challenging because of the non-convex natu...
[ { "from": "human", "value": "Suppose\n$$\\begin{align*}\r\n\\min A &\\mathrm{vec}(U) \\\\\r\n&\\text{subject to } U_{i,j} \\leq \\max\\{U_{i,k}, U_{k,j}\\}, \\quad i,j,k = 1, \\ldots, n\r\n\\end{align*}$$\nwhere $U$ is a symmetric $n\\times n$ matrix, and $\\mathrm{vec}(U)$ reshapes $U$ into a one-dimension...
I have a data set $x_{1}, x_{2}, \ldots, x_{k}$ and want to find the parameter $m$ such that it minimizes the sum $$\sum_{i=1}^{k}\big|m-x_i\big|.$$ that is $$\min_{m}\sum_{i=1}^{k}\big|m-x_i\big|.$$
To minimize the sum \[ S(m) = \sum_{i=1}^{k} |m - x_i|, \] we can recognize that this is an optimization problem involving absolute values, which is associated with finding the median of the data set \(x_1, x_2, \ldots, x_k\). ### Key Observations: 1. **Behavior of the Absolute Value**: The expression \(|m - x_i|\...
[ { "from": "human", "value": "I have a data set $x_{1}, x_{2}, \\ldots, x_{k}$ and want to find the parameter $m$ such that it minimizes the sum $$\\sum_{i=1}^{k}\\big|m-x_i\\big|.$$ \nthat is\n$$\\min_{m}\\sum_{i=1}^{k}\\big|m-x_i\\big|.$$\n" }, { "from": "gpt", "value": "To minimize the sum \n\...
This question is an extension of two discussions that came up recently in the replies to "C++ vs Fortran for HPC". And it is a bit more of a challenge than a question... One of the most often-heard arguments in favor of Fortran is that the compilers are just better. Since most C/Fortran compilers share the same back en...
Your investigation into the performance of C and Fortran for the DAXPY operation, as well as the matrix multiplication tests, raises important points regarding compiler optimization and language capabilities. Here are some insights and suggestions based on your findings and updates: ### Compiler Optimizations 1. **Ve...
[ { "from": "human", "value": "This question is an extension of two discussions that came up recently in the replies to \"C++ vs Fortran for HPC\". And it is a bit more of a challenge than a question...\nOne of the most often-heard arguments in favor of Fortran is that the compilers are just better. Since mos...
We have Maui and Torque on our lab's UNIX cluster. Right now, all jobs are served by FIFO. We'd like to implement a more fair policy, but I have not successfully implemented it. The online documentation was not quite clear, and nothing that I've tried to implement has had any effect (I've altered the config file, then ...
To implement a fair scheduling policy on your UNIX cluster using Maui and Torque, you'll want to move beyond the default FIFO policy. Here are some steps to guide you through the process of changing the scheduling policy in Maui, as well as some tips for troubleshooting: ### Steps to Change Scheduling Policy 1. **Edi...
[ { "from": "human", "value": "We have Maui and Torque on our lab's UNIX cluster. Right now, all jobs are served by FIFO. We'd like to implement a more fair policy, but I have not successfully implemented it. The online documentation was not quite clear, and nothing that I've tried to implement has had any ef...
Wherever I have seen, PETSc tutorial/documents etc. say that it is useful for linear algebra and usually specifies that sparse systems will benefit. What about dense matrices? I am concerned about solving $Ax=b$ for dense $A$. I have written my own code for CG and QMR in Fortran. The basic construct is to rip apart the...
PETSc (Portable, Extensible Toolkit for Scientific Computation) is a powerful library designed for the scalable solution of linear and nonlinear problems, particularly focused on large sparse systems typical in scientific computing. However, it is indeed capable of handling dense matrices as well. Here are some insight...
[ { "from": "human", "value": "Wherever I have seen, PETSc tutorial/documents etc. say that it is useful for linear algebra and usually specifies that sparse systems will benefit. What about dense matrices? I am concerned about solving $Ax=b$ for dense $A$.\nI have written my own code for CG and QMR in Fortra...
I just installed the PETSc library. This is what I did from the home directory ~ gunzip -c petsc-3.2-p6.tar.gz|tar -xof - cd ~/petsc-3.2-p6 PETC_DIR=$PWD: export PETSC_DIR ./configure --download-f-blas-lapack=1 make all make PETSC_DIR=/export/home/myusername/petsc-3.2-p6 PETSC_ARCH=arch-linux2-c-debug test (note: I d...
The error you are encountering indicates that the makefile in the `~/petsc-3.2-p6/src/snes/examples/tutorials` directory is trying to include certain configuration files (like `variables`, `rules`, and `test`) that it cannot find. This usually happens when the environment variables for PETSc are not set correctly or if...
[ { "from": "human", "value": "I just installed the PETSc library. This is what I did from the home directory ~\ngunzip -c petsc-3.2-p6.tar.gz|tar -xof -\ncd ~/petsc-3.2-p6\nPETC_DIR=$PWD: export PETSC_DIR\n./configure --download-f-blas-lapack=1\nmake all\nmake PETSC_DIR=/export/home/myusername/petsc-3.2-p6 ...