README: document trt_v12 TensorRT per-SM builder resources

README.md

@@ -2,10 +2,11 @@
 license: other
 license_name: nvidia-cuda-cudnn-redistributable
 license_link: https://docs.nvidia.com/cuda/eula/index.html
-pretty_name: MBFS CUDA Runtime Bundle (cuda_v12 + cuda_v11)
+pretty_name: MBFS CUDA + TensorRT Runtime Bundle (cuda_v12 + cuda_v11 + trt_v12)
 tags:
   - cuda
   - cudnn
+  - tensorrt
   - onnxruntime
   - runtime-libraries
   - windows
@@ -28,9 +29,20 @@ must still use `cu11` (loading `cu12` binaries fails with
 `scripts/build_windows.py` clamps the stack to the lower of the GPU and driver
 ceilings (override with `--gpu-stack`).
 
-> ⚠️ These are **runtime redistributable libraries**, not source. The CUDA and
-> cuDNN DLLs are © NVIDIA Corporation and remain under NVIDIA's licenses — see
-> **[License & redistribution](#license--redistribution)** below.
+**TensorRT engine-build libraries** live in a *companion* folder,
+[`trt_v12/`](./trt_v12) (for the `cu12` stack). These are the TensorRT 10
+runtime + parser (`nvinfer*`, `nvonnxparser`) and the per-SM **builder
+resources** used when TensorRT compiles an engine. It is **not** a standalone
+CUDA stack — pair it with `cuda_v12/` (whose `onnxruntime_providers_tensorrt.dll`
+is only the small ONNX Runtime ↔ TensorRT bridge). Unlike the CUDA folders,
+`trt_v12/` is fetched **selectively**: a build downloads only the one builder
+resource matching the target GPU's compute capability (plus the always-included
+PTX fallback), not the whole ~2.8 GiB set. See
+**[Contents (`trt_v12/`)](#contents-trt_v12)**.
+
+> ⚠️ These are **runtime redistributable libraries**, not source. The CUDA,
+> cuDNN, and TensorRT DLLs are © NVIDIA Corporation and remain under NVIDIA's
+> licenses — see **[License & redistribution](#license--redistribution)** below.
 
 ## Contents (`cuda_v12/`)
 
@@ -70,6 +82,45 @@ ceilings (override with `--gpu-stack`).
 > must be used together (never mix DLLs across folders or with another ONNX
 > Runtime release, or the CUDA EP fails to load).
 
+## Contents (`trt_v12/`)
+
+TensorRT 10 for the `cu12` stack, split into **core** (always needed) and
+**per-SM builder resources** (one per GPU architecture). A build pulls the core
+plus **only** the resource matching the target GPU's compute capability, plus
+the PTX fallback — typically ≈ 1.0–1.7 GiB instead of the full ≈ 2.8 GiB.
+
+**Core — always downloaded:**
+
+| File | Component | Approx. size |
+|---|---|---|
+| `nvinfer_10.dll` | TensorRT 10 core inference runtime + builder | 432 MB |
+| `nvinfer_plugin_10.dll` | TensorRT 10 standard plugins | 53 MB |
+| `nvonnxparser_10.dll` | ONNX → TensorRT network parser | 3 MB |
+| `nvrtc64_120_0.dll` | NVRTC runtime compiler (CUDA 12) | 44 MB |
+
+**Per-SM builder resources — download only the one matching your GPU:**
+
+| File | Architecture | Example GPUs | Approx. size |
+|---|---|---|---|
+| `nvinfer_builder_resource_ptx_10.dll` | **PTX JIT fallback — always included** | (any, forward-compat) | 488 MB |
+| `nvinfer_builder_resource_sm75_10.dll` | Turing | T4, RTX 20xx | 157 MB |
+| `nvinfer_builder_resource_sm80_10.dll` | Ampere | A100, A30 | 256 MB |
+| `nvinfer_builder_resource_sm86_10.dll` | Ampere | A40, RTX 30xx | 241 MB |
+| `nvinfer_builder_resource_sm89_10.dll` | Ada | L4, L40, RTX 40xx | 254 MB |
+| `nvinfer_builder_resource_sm90_10.dll` | Hopper | H100, H200 | 661 MB |
+| `nvinfer_builder_resource_sm120_10.dll` | Blackwell | B100/B200, RTX 50xx | 377 MB |
+
+**Full set ≈ 2.8 GiB** (4 core + 7 resources). Example single-SM footprint —
+Ampere A30 (sm80): core (532 MB) + PTX (488 MB) + `sm80` (256 MB) ≈ **1.2 GiB**.
+
+> The builder resources are only needed when TensorRT **compiles** an engine
+> (the first run for a given model/GPU). `nvinfer_10.dll` loads the matching
+> `nvinfer_builder_resource_sm<cc>_10.dll` from the DLL search path at
+> engine-build time; the MBFS Sentinel build stages them under
+> `dist/lib/trt_v12/` and adds that directory to the process `PATH`. Once an
+> engine cache (`.engine`/`.trt`) exists, the resource for that SM is no longer
+> read.
+
 ## Requirements
 
 - **OS:** Windows x64
@@ -98,6 +149,11 @@ forward-compatibility** to newer archs):
 | 9.0a | Hopper | H100, H200 | ✅ |
 | 10.x / 12.x | **Blackwell** | B100/B200, RTX 50xx | ❌ not native |
 
+For the **TensorRT** path the per-SM builder resources in `trt_v12/` cover
+`sm75 / sm80 / sm86 / sm89 / sm90 / sm120`; older archs (sm_52/60/70) fall back
+to the PTX builder resource (JIT). Pick the resource by compute capability:
+`sm = major*10 + minor` (e.g. 8.0 → `sm80`, 12.0 → `sm120`).
+
 ### `cu11`
 
 The `cu11` stack is the fallback for machines that predate CUDA 12: NVIDIA
@@ -114,8 +170,9 @@ CUDA path only.
 ## Usage
 
 The MBFS Sentinel build pulls the right stack automatically
-(`build_windows.py --gpu-stack {cu12|cu11} --cuda-source hf`). To fetch a stack
-manually:
+(`build_windows.py --gpu-stack {cu12|cu11} --cuda-source hf`), including the
+matching TensorRT builder resource (`--tensorrt-source hf`, default). To fetch a
+stack manually:
 
 ```bash
 # cu12 into ./dist/lib (lands at ./dist/lib/cuda_v12/)
@@ -127,6 +184,20 @@ hf download MBFSAITeam/cuda-runtime-bundle --repo-type dataset \
   --include "cuda_v11/*" --local-dir ./dist/lib
 ```
 
+For TensorRT, fetch the **core + PTX + only your GPU's SM** instead of the whole
+folder (example for an Ampere A30, sm80):
+
+```bash
+hf download MBFSAITeam/cuda-runtime-bundle --repo-type dataset \
+  --include "trt_v12/nvinfer_10.dll" \
+  --include "trt_v12/nvinfer_plugin_10.dll" \
+  --include "trt_v12/nvonnxparser_10.dll" \
+  --include "trt_v12/nvrtc64_120_0.dll" \
+  --include "trt_v12/nvinfer_builder_resource_ptx_10.dll" \
+  --include "trt_v12/nvinfer_builder_resource_sm80_10.dll" \
+  --local-dir ./dist/lib
+```
+
 For reproducible builds, pin a commit revision with `--revision <sha>` instead of
 `main`.
 
@@ -135,13 +206,17 @@ For reproducible builds, pin a commit revision with `--revision <sha>` instead o
 This repository bundles components under **different licenses**:
 
 - **ONNX Runtime** (`onnxruntime*.dll`) — MIT License, © Microsoft.
-- **CUDA runtime** (`cudart`, `cublas`, `cublasLt`, `cufft`, `curand`, `cusparse`)
-  — © NVIDIA Corporation, redistributed under the
+- **CUDA runtime** (`cudart`, `cublas`, `cublasLt`, `cufft`, `curand`, `cusparse`,
+  `nvrtc`) — © NVIDIA Corporation, redistributed under the
   [NVIDIA CUDA Toolkit EULA](https://docs.nvidia.com/cuda/eula/index.html).
 - **cuDNN** (`cudnn*.dll`, both v8 and v9) — © NVIDIA Corporation, redistributed
   under the [NVIDIA cuDNN Software License Agreement](https://docs.nvidia.com/deeplearning/cudnn/sla/index.html).
+- **TensorRT** (`nvinfer*.dll`, `nvonnxparser*.dll`, and the
+  `nvinfer_builder_resource_*` builder resources) — © NVIDIA Corporation,
+  redistributed under the
+  [NVIDIA TensorRT Software License Agreement](https://docs.nvidia.com/deeplearning/tensorrt/sla/index.html).
 
 The NVIDIA libraries are redistributed **unmodified** as runtime dependencies, as
-permitted by the above agreements. NVIDIA, CUDA, and cuDNN are trademarks of NVIDIA
-Corporation. This repository is not affiliated with or endorsed by NVIDIA. By using
-these files you agree to the respective NVIDIA license terms.
+permitted by the above agreements. NVIDIA, CUDA, cuDNN, and TensorRT are trademarks
+of NVIDIA Corporation. This repository is not affiliated with or endorsed by NVIDIA.
+By using these files you agree to the respective NVIDIA license terms.