diff --git a/.gitattributes b/.gitattributes
index bed0738c7eeb449bca98b5d2f33c89a1ee56349a..176b812f572a331a0dd28d60e5fb060f3d8d7485 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -58,3 +58,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+results/jobs/20261006-100132-pure-pursuit/episodes.jsonl filter=lfs diff=lfs merge=lfs -text
diff --git a/results/index/episodes.jsonl b/results/index/episodes.jsonl
index 741059253aec8c16fb73b6f61890363fedfa22ad..c139f2323371a5925e05725a873de40a237a0aa8 100644
--- a/results/index/episodes.jsonl
+++ b/results/index/episodes.jsonl
@@ -780,3 +780,10695 @@
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 {"key": "815d1e80a71241a6d1a3adb098adb145bf5bab78b04f432b6593b3851988b3fe", "job_id": "20261005-165451-stack-default", "shard": "jobs/20261005-165451-stack-default/logs/shard-0010.jsonl.gz"}
 {"key": "faf9694b5d21d882a64e291dc7c7eb8e9cae38041a2840c21eb89035e9964ddd", "job_id": "20261005-165451-stack-default", "shard": "jobs/20261005-165451-stack-default/logs/shard-0010.jsonl.gz"}
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diff --git a/results/jobs/20261006-100132-pure-pursuit/breakdown.json b/results/jobs/20261006-100132-pure-pursuit/breakdown.json
new file mode 100644
index 0000000000000000000000000000000000000000..61f179236b9aaa462d0ceb05da49dc160701d51f
--- /dev/null
+++ b/results/jobs/20261006-100132-pure-pursuit/breakdown.json
@@ -0,0 +1,84260 @@
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+    ]
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+  }
+ }
+}
\ No newline at end of file
diff --git a/results/jobs/20261006-100132-pure-pursuit/episodes.jsonl b/results/jobs/20261006-100132-pure-pursuit/episodes.jsonl
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+size 56538667
diff --git a/results/jobs/20261006-100132-pure-pursuit/gautschi/0/done.txt b/results/jobs/20261006-100132-pure-pursuit/gautschi/0/done.txt
new file mode 100644
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diff --git a/results/jobs/20261006-100132-pure-pursuit/gautschi/0/episodes.json b/results/jobs/20261006-100132-pure-pursuit/gautschi/0/episodes.json
new file mode 100644
index 0000000000000000000000000000000000000000..2d28b0e60ada55e391494cae11d140d9afaaa274
--- /dev/null
+++ b/results/jobs/20261006-100132-pure-pursuit/gautschi/0/episodes.json
@@ -0,0 +1 @@
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"fixed_white_m": 0.002, "error_scale": 1.0, "latency_ms": 60.0, "rate_hz": 20.0, "float_dwell_scale": 1.0, "outages": false, "wrong_fix": false, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 0.3, "dlpf_hz": 0}, "wheel": {"white_mps": 0.03, "scale_error": 0.01, "rate_hz": 100.0}, "steer_encoder": {"enabled": false, "resolution_deg": 0.35, "white_deg": 0.2, "rate_hz": 50.0}}, "system_frequency": 60}, "kart_name": "kart1", "condition": "sensors_medium_steer_low", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 4100633408, "tier": "large", "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"}}, {"key": "7552cfd7ff1f5fb72c519f5246c741917119b4f0e5d9af8a541ed1e5d3120348", "resolved": {"kart": {"name": "kart3", "chrono_dir": "chrono/kart3", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 142.0, "travel_deg": 70.0, "step_deg": 0.9, "slop_deg": 1.7, "center_offset_deg": 0.0, "position_uncertainty_deg": 0.5}, "actuator": {"latency_ms": 240.0, "drive_tau_s": 0.41, "steer_latency_ms": 60.0}, "sensors": {"gps": {"enabled": true, "fix_chain": "measured", "fixed_gm_sigma_m": 0.006, "fixed_gm_tau_s": 7.0, "fixed_white_m": 0.002, "error_scale": 1.0, "latency_ms": 60.0, "rate_hz": 20.0, "float_dwell_scale": 1.0, "outages": false, "wrong_fix": false, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 0.3, "dlpf_hz": 0}, "wheel": {"white_mps": 0.03, "scale_error": 0.01, "rate_hz": 100.0}, "steer_encoder": {"enabled": false, "resolution_deg": 0.35, "white_deg": 0.2, "rate_hz": 50.0}}, "system_frequency": 60}, "kart_name": "kart3", "condition": "sensors_medium_steer_low", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 883802097, "tier": "large", "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"}}, {"key": "c6f1333ea55650e8af5b872a02ea055677b54602aaa0d39e6f76c3e6bd803194", "resolved": {"kart": {"name": "kart2", "chrono_dir": "chrono/kart2", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 70.0, "travel_deg": 70.0, "step_deg": 0.9, "slop_deg": 5.0, "center_offset_deg": 0.4, "position_uncertainty_deg": 1.0}, "actuator": {"latency_ms": 240.0, "drive_tau_s": 0.41, "steer_latency_ms": 60.0}, "sensors": {"gps": {"enabled": true, "fix_chain": "measured", "fixed_gm_sigma_m": 0.006, "fixed_gm_tau_s": 7.0, "fixed_white_m": 0.002, "error_scale": 1.0, "latency_ms": 60.0, "rate_hz": 20.0, "float_dwell_scale": 1.0, "outages": false, "wrong_fix": false, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 0.3, "dlpf_hz": 0}, "wheel": {"white_mps": 0.03, "scale_error": 0.01, "rate_hz": 100.0}, "steer_encoder": {"enabled": false, "resolution_deg": 0.35, "white_deg": 0.2, "rate_hz": 50.0}}, "system_frequency": 60}, "kart_name": "kart2", "condition": "sensors_medium_steer_medium", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 970488497, "tier": "large", "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"}}]
\ No newline at end of file
diff --git a/results/jobs/20261006-100132-pure-pursuit/gautschi/0/gautschi_launch.py b/results/jobs/20261006-100132-pure-pursuit/gautschi/0/gautschi_launch.py
new file mode 100644
index 0000000000000000000000000000000000000000..bf8e0fad5f2b6ef416b2f1d3b27679a56f888d15
--- /dev/null
+++ b/results/jobs/20261006-100132-pure-pursuit/gautschi/0/gautschi_launch.py
@@ -0,0 +1,143 @@
+"""Runs on a Gautschi node (stdlib only): episodes from a queue in parallel workers, one contained Apptainer per episode."""
+import argparse
+import json
+import os
+import queue
+import shutil
+import subprocess
+import threading
+import time
+
+RUN = ("source /opt/ros/humble/setup.bash && source /ws/install/setup.bash"
+       " && python3 -m simnode.batch /batch.json /out")
+CUDA_LIB = "/ws/mpc_cuda/libmpc_cuda.so"   # built per stack by runner/gautschi.build_stack for gautschi-gpu
+SAMPLE_S = 15
+STAGGER_S = 0.25   # between worker starts: the dev job's one error was a stack starved in the 96-way start burst
+EPISODE_TIMEOUT_S = 1200   # about 4x the slowest lap; a killed episode has no outcome and is retried by the host
+
+
+def worker_cmd(i, work, out, ep, sif, engine, stack, gpu=None):
+    """Private /tmp, HOME, /dev/shm, IPC, PIDs and loopback per episode, plus a distinct ROS_DOMAIN_ID per worker;
+    gpu (a host CUDA device) adds the driver and the stack's CUDA MPC kernel."""
+    cuda = ["--nv", "--env", f"CUDA_VISIBLE_DEVICES={gpu}", "--env", f"MPC_CUDA_LIB={CUDA_LIB}"] if gpu is not None else []
+    return ["apptainer", "exec", *cuda, "--contain", "--cleanenv", "--ipc", "--pid", "--net", "--network", "none", "--workdir", work,
+            "--env", f"ROS_DOMAIN_ID={i + 1}", "--env", "ROS_HOME=/tmp/ros", "--env", "TMPDIR=/tmp",
+            "--bind", f"{engine}:/opt/sim:ro", "--bind", f"{stack}:/ws:ro", "--bind", f"{out}:/out",
+            "--bind", f"{ep}:/batch.json:ro", sif, "bash", "-lc", RUN]
+
+
+def parse_smi(text):
+    """nvidia-smi 'utilization.gpu, memory.used' csv rows to per-GPU lists."""
+    rows = [[int(v) for v in ln.split(",")] for ln in text.strip().splitlines() if ln.strip()]
+    return {"gpu_util": [r[0] for r in rows], "gpu_mem_mib": [r[1] for r in rows]}
+
+
+def _solver(logdir):
+    """pathfinder's 'MPC solver: ...' and CUDA fallback lines from the episode's ROS logs."""
+    lines = []
+    for dp, _, fns in os.walk(logdir):
+        for fn in fns:
+            try:
+                with open(os.path.join(dp, fn), errors="replace") as f:
+                    lines += [ln.strip() for ln in f if "MPC solver:" in ln or "CUDA MPC unavailable" in ln]
+            except OSError:
+                pass
+    return "\n".join(dict.fromkeys(lines))
+
+
+def main(argv=None):
+    p = argparse.ArgumentParser()
+    for a in ("episodes", "out", "sif", "engine", "stack", "work", "timeline", "done"):
+        p.add_argument("--" + a, required=True)
+    p.add_argument("--workers", type=int, required=True)
+    p.add_argument("--gpus", type=int, default=0)
+    a = p.parse_args(argv)
+    with open(a.episodes) as f:
+        q = queue.Queue()
+        for e in json.load(f):   # the host already ordered them, longest first
+            q.put(e)
+    os.makedirs(a.out, exist_ok=True)
+    lock, t0 = threading.Lock(), time.time()
+    devs = [d for d in os.environ.get("CUDA_VISIBLE_DEVICES", "").split(",") if d][:a.gpus] or [str(n) for n in range(a.gpus)]
+
+    def log(**ev):
+        with lock, open(a.timeline, "a") as f:
+            f.write(json.dumps(dict(ev, t=round(time.time() - t0, 3))) + "\n")
+
+    def worker(i):
+        time.sleep(i * STAGGER_S)
+        while True:
+            try:
+                e = q.get_nowait()
+            except queue.Empty:
+                return
+            key, work = e["key"], os.path.join(a.work, e["key"])
+            stage, ep = os.path.join(work, "stage"), os.path.join(work, "ep.json")
+            os.makedirs(stage)
+            with open(ep, "w") as f:
+                json.dump([e], f)
+            log(ev="start", key=key, worker=i)
+            gpu = devs[i % len(devs)] if devs and e["resolved"].get("recipe", {}).get("sim", {}).get("cuda") else None
+            limit = EPISODE_TIMEOUT_S * max(1, e["resolved"]["scenario"].get("laps", 1))   # per lap: 5-lap episodes run 5x longer
+            try:
+                rc = subprocess.run(worker_cmd(i, work, stage, ep, a.sif, a.engine, a.stack, gpu), stdout=subprocess.DEVNULL,
+                                    stderr=subprocess.DEVNULL, timeout=limit).returncode
+            except subprocess.TimeoutExpired:
+                rc = "timeout"
+            solver = _solver(os.path.join(work, "tmp", "ros", "log"))
+            if solver and os.path.isdir(os.path.join(stage, key)):
+                with open(os.path.join(stage, key, "solver.txt"), "w") as f:
+                    f.write(solver + "\n")
+            if os.path.exists(os.path.join(stage, key, "outcome.json")):
+                tmp, dst = os.path.join(a.out, ".tmp-" + key), os.path.join(a.out, key)
+                shutil.rmtree(tmp, ignore_errors=True)
+                shutil.copytree(os.path.join(stage, key), tmp)
+                shutil.rmtree(dst, ignore_errors=True)
+                os.rename(tmp, dst)   # the host's rsync sees a key only once its directory is complete
+                with lock, open(a.done, "a") as f:
+                    f.write(key + "\n")
+            shutil.rmtree(work, ignore_errors=True)
+            log(ev="end", key=key, worker=i, rc=rc, gpu=gpu,
+                solver=solver.split("MPC solver: ")[-1] if "MPC solver: " in solver else solver or None)
+
+    def sampler(stop):
+        """Job CPU use from its cgroup, as busy cores, every SAMPLE_S."""
+        try:
+            with open("/proc/self/cgroup") as f:
+                path = "/sys/fs/cgroup" + f.read().strip().split(":")[-1] + "/cpu.stat"
+            prev = None
+            while not stop.wait(SAMPLE_S if prev else 0):
+                with open(path) as f:
+                    use = next(int(ln.split()[1]) for ln in f if ln.startswith("usage_usec"))
+                now = time.time()
+                if prev:
+                    log(ev="cpu", busy_cores=round((use - prev[0]) / 1e6 / (now - prev[1]), 2))
+                prev = (use, now)
+        except (OSError, StopIteration, ValueError):
+            pass
+
+    def gpu_sampler(stop):
+        """GPU utilisation and memory of the job's GPUs, every SAMPLE_S."""
+        while not stop.wait(SAMPLE_S):
+            try:
+                p = subprocess.Popen(["nvidia-smi", "--query-gpu=utilization.gpu,memory.used", "--format=csv,noheader,nounits"],
+                                     stdout=subprocess.PIPE, stderr=subprocess.DEVNULL, text=True)
+                log(ev="gpu", **parse_smi(p.communicate(timeout=30)[0]))
+            except Exception:   # no driver or a hung query: skip this sample
+                pass
+
+    cores = len(os.sched_getaffinity(0)) if hasattr(os, "sched_getaffinity") else os.cpu_count()
+    log(ev="launch", workers=a.workers, cores=cores)
+    stop = threading.Event()
+    threads = [threading.Thread(target=worker, args=(i,)) for i in range(a.workers)]
+    samplers = [sampler] + ([gpu_sampler] if a.gpus else [])
+    for t in threads + [threading.Thread(target=f, args=(stop,), daemon=True) for f in samplers]:
+        t.start()
+    for t in threads:
+        t.join()
+    stop.set()
+    log(ev="done")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/results/jobs/20261006-100132-pure-pursuit/gautschi/0/sbatch.sh b/results/jobs/20261006-100132-pure-pursuit/gautschi/0/sbatch.sh
new file mode 100644
index 0000000000000000000000000000000000000000..7e6e3a33ee7a919b50d0206b19d71e4b8eb0a4dd
--- /dev/null
+++ b/results/jobs/20261006-100132-pure-pursuit/gautschi/0/sbatch.sh
@@ -0,0 +1,5 @@
+#!/bin/bash
+#SBATCH -p highmem -A lilly-rob1 -N 1 -n 1 -c 192 --time 86 -J AutoSim-large-pure-pursuit-1 --comment 20261006-100132-pure-pursuit -o AutoSim/jobs/20261006-100132-pure-pursuit/0/slurm-%j.out
+W=/dev/shm/AutoSim-$SLURM_JOB_ID
+trap 'rm -rf "$W"' EXIT
+python3 $HOME/AutoSim/jobs/20261006-100132-pure-pursuit/0/gautschi_launch.py --episodes $HOME/AutoSim/jobs/20261006-100132-pure-pursuit/0/episodes.json --out $HOME/AutoSim/out/20261006-100132-pure-pursuit --sif $HOME/AutoSim/images/AutoSim-99d206f40cb1.sif --engine $HOME/AutoSim/engine/d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f --stack $HOME/AutoSim/stacks/9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d --workers 96 --work $W --timeline $HOME/AutoSim/jobs/20261006-100132-pure-pursuit/0/timeline.jsonl --done $HOME/AutoSim/jobs/20261006-100132-pure-pursuit/0/done.txt
diff --git a/results/jobs/20261006-100132-pure-pursuit/gautschi/1/done.txt b/results/jobs/20261006-100132-pure-pursuit/gautschi/1/done.txt
new file mode 100644
index 0000000000000000000000000000000000000000..792bba717baf1d1354e7a528caac997ba6e6df03
--- /dev/null
+++ b/results/jobs/20261006-100132-pure-pursuit/gautschi/1/done.txt
@@ -0,0 +1,5346 @@
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diff --git a/results/jobs/20261006-100132-pure-pursuit/gautschi/1/episodes.json b/results/jobs/20261006-100132-pure-pursuit/gautschi/1/episodes.json
new file mode 100644
index 0000000000000000000000000000000000000000..a68d3dc148001e0b2163fc4c7e883116cecef92d
--- /dev/null
+++ b/results/jobs/20261006-100132-pure-pursuit/gautschi/1/episodes.json
@@ -0,0 +1 @@
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"condition": "sensors_low_steer_low", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 3550144860, "tier": "large", "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"}}, {"key": "e1a4b5b33d9e66bf1d9113629495054b3c800de7cf935b5712abcabca26cfb9a", "resolved": {"kart": {"name": "kart3", "chrono_dir": "chrono/kart3", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 142.0, "travel_deg": 70.0, "step_deg": 0.9, "slop_deg": 1.7, "center_offset_deg": 0.0, "position_uncertainty_deg": 0.5}, "actuator": {"latency_ms": 240.0, "drive_tau_s": 0.41, "steer_latency_ms": 60.0}, "sensors": {"gps": {"enabled": true, "fix_chain": "always_fixed", "fixed_gm_sigma_m": 0.006, "fixed_gm_tau_s": 7.0, "fixed_white_m": 0.002, "error_scale": 1.0, "latency_ms": 20.0, "rate_hz": 20.0, "float_dwell_scale": 1.0, "outages": false, "wrong_fix": false, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 0.1, "dlpf_hz": 44}, "wheel": {"white_mps": 0.01, "scale_error": 0.0, "rate_hz": 100.0}, "steer_encoder": {"enabled": false, "resolution_deg": 0.35, "white_deg": 0.2, "rate_hz": 50.0}}, "system_frequency": 60}, "kart_name": "kart3", "condition": "sensors_low_steer_low", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 489805293, "tier": "large", "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"}}, {"key": "3e3a9b351f9ab9ad1f6ffd045a97d566e1ed0ce7355b45dbdb9c9638ca6d24ef", "resolved": {"kart": {"name": "kart2", "chrono_dir": "chrono/kart2", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 70.0, "travel_deg": 70.0, "step_deg": 0.9, "slop_deg": 5.0, "center_offset_deg": 0.4, "position_uncertainty_deg": 1.0}, "actuator": {"latency_ms": 240.0, "drive_tau_s": 0.41, "steer_latency_ms": 60.0}, "sensors": {"gps": {"enabled": true, "fix_chain": "always_fixed", "fixed_gm_sigma_m": 0.006, "fixed_gm_tau_s": 7.0, "fixed_white_m": 0.002, "error_scale": 1.0, "latency_ms": 20.0, "rate_hz": 20.0, "float_dwell_scale": 1.0, "outages": false, "wrong_fix": false, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 0.1, "dlpf_hz": 44}, "wheel": {"white_mps": 0.01, "scale_error": 0.0, "rate_hz": 100.0}, "steer_encoder": {"enabled": false, "resolution_deg": 0.35, "white_deg": 0.2, "rate_hz": 50.0}}, "system_frequency": 60}, "kart_name": "kart2", "condition": "sensors_low_steer_medium", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 4249680720, "tier": "large", "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"}}, {"key": "584b5d24a479436cb01ad42d3547d59634a0f2007b589b7e218cf0ac1b424b82", "resolved": {"kart": {"name": "kart1", "chrono_dir": "chrono/kart", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 20.02, "travel_deg": 70.0, "step_deg": 0.9, "slop_deg": 10.0, "center_offset_deg": 2.0, "position_uncertainty_deg": 2.0}, "actuator": {"latency_ms": 240.0, "drive_tau_s": 0.41, "steer_latency_ms": 60.0}, "sensors": {"gps": {"enabled": true, "fix_chain": "measured", "fixed_gm_sigma_m": 0.006, "fixed_gm_tau_s": 7.0, "fixed_white_m": 0.002, "error_scale": 1.0, "latency_ms": 60.0, "rate_hz": 20.0, "float_dwell_scale": 1.0, "outages": false, "wrong_fix": false, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 0.3, "dlpf_hz": 0}, "wheel": {"white_mps": 0.03, "scale_error": 0.01, "rate_hz": 100.0}, "steer_encoder": {"enabled": false, "resolution_deg": 0.35, "white_deg": 0.2, "rate_hz": 50.0}}, "system_frequency": 60}, "kart_name": "kart1", "condition": "sensors_medium_steer_high", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 4074836692, "tier": "large", "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"}}, {"key": "142d535ec300c21140440c3993f8b03a4a497a51fafae6fc6cda87c312bc079e", "resolved": {"kart": {"name": "kart3", "chrono_dir": "chrono/kart3", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 20.305999999999997, "travel_deg": 70.0, "step_deg": 0.9, "slop_deg": 11.5, "center_offset_deg": 2.0, "position_uncertainty_deg": 2.0}, "actuator": {"latency_ms": 240.0, "drive_tau_s": 0.41, "steer_latency_ms": 60.0}, "sensors": {"gps": {"enabled": true, "fix_chain": "measured", "fixed_gm_sigma_m": 0.006, "fixed_gm_tau_s": 7.0, "fixed_white_m": 0.002, "error_scale": 1.0, "latency_ms": 60.0, "rate_hz": 20.0, "float_dwell_scale": 1.0, "outages": false, "wrong_fix": false, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 0.3, "dlpf_hz": 0}, "wheel": {"white_mps": 0.03, "scale_error": 0.01, "rate_hz": 100.0}, "steer_encoder": {"enabled": false, "resolution_deg": 0.35, "white_deg": 0.2, "rate_hz": 50.0}}, "system_frequency": 60}, "kart_name": "kart3", "condition": "sensors_medium_steer_high", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 4179301858, "tier": "large", "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"}}, {"key": "a99a325891713e46c585d621c55d52b6543d3b73482cda401a5d6379ff9874d5", "resolved": {"kart": {"name": "kart2", "chrono_dir": "chrono/kart2", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 140.0, "travel_deg": 70.0, "step_deg": 0.9, "slop_deg": 0.2, "center_offset_deg": 0.0, "position_uncertainty_deg": 0.5}, "actuator": {"latency_ms": 240.0, "drive_tau_s": 0.41, "steer_latency_ms": 60.0}, "sensors": {"gps": {"enabled": true, "fix_chain": "measured", "fixed_gm_sigma_m": 0.006, "fixed_gm_tau_s": 7.0, "fixed_white_m": 0.002, "error_scale": 1.0, "latency_ms": 60.0, "rate_hz": 20.0, "float_dwell_scale": 1.0, "outages": false, "wrong_fix": false, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 0.3, "dlpf_hz": 0}, "wheel": {"white_mps": 0.03, "scale_error": 0.01, "rate_hz": 100.0}, "steer_encoder": {"enabled": false, "resolution_deg": 0.35, "white_deg": 0.2, "rate_hz": 50.0}}, "system_frequency": 60}, "kart_name": "kart2", "condition": "sensors_medium_steer_low", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 3186302859, "tier": "large", "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"}}, {"key": "4830be8b451713c150c89416bd526796e9233a55d23673cd6cfb8548aaea0f15", "resolved": {"kart": {"name": "kart1", "chrono_dir": "chrono/kart", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 70.0, "travel_deg": 70.0, "step_deg": 0.9, "slop_deg": 5.0, "center_offset_deg": 0.4, "position_uncertainty_deg": 1.0}, "actuator": {"latency_ms": 240.0, "drive_tau_s": 0.41, "steer_latency_ms": 60.0}, "sensors": {"gps": {"enabled": true, "fix_chain": "measured", "fixed_gm_sigma_m": 0.006, "fixed_gm_tau_s": 7.0, "fixed_white_m": 0.002, "error_scale": 1.0, "latency_ms": 60.0, "rate_hz": 20.0, "float_dwell_scale": 1.0, "outages": false, "wrong_fix": false, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 0.3, "dlpf_hz": 0}, "wheel": {"white_mps": 0.03, "scale_error": 0.01, "rate_hz": 100.0}, "steer_encoder": {"enabled": false, "resolution_deg": 0.35, "white_deg": 0.2, "rate_hz": 50.0}}, "system_frequency": 60}, "kart_name": "kart1", "condition": "sensors_medium_steer_medium", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 362170483, "tier": "large", "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"}}, {"key": "166fbee08b978636df04708184d0c1b2ca49529cfdf6c90bc01aabfb6bb0cb07", "resolved": {"kart": {"name": "kart3", "chrono_dir": "chrono/kart3", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 71.0, "travel_deg": 70.0, "step_deg": 0.9, "slop_deg": 6.5, "center_offset_deg": 0.4, "position_uncertainty_deg": 1.0}, "actuator": {"latency_ms": 240.0, "drive_tau_s": 0.41, "steer_latency_ms": 60.0}, "sensors": {"gps": {"enabled": true, "fix_chain": "measured", "fixed_gm_sigma_m": 0.006, "fixed_gm_tau_s": 7.0, "fixed_white_m": 0.002, "error_scale": 1.0, "latency_ms": 60.0, "rate_hz": 20.0, "float_dwell_scale": 1.0, "outages": false, "wrong_fix": false, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 0.3, "dlpf_hz": 0}, "wheel": {"white_mps": 0.03, "scale_error": 0.01, "rate_hz": 100.0}, "steer_encoder": {"enabled": false, "resolution_deg": 0.35, "white_deg": 0.2, "rate_hz": 50.0}}, "system_frequency": 60}, "kart_name": "kart3", "condition": "sensors_medium_steer_medium", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 3171405895, "tier": "large", "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"}}]
\ No newline at end of file
diff --git a/results/jobs/20261006-100132-pure-pursuit/gautschi/1/gautschi_launch.py b/results/jobs/20261006-100132-pure-pursuit/gautschi/1/gautschi_launch.py
new file mode 100644
index 0000000000000000000000000000000000000000..bf8e0fad5f2b6ef416b2f1d3b27679a56f888d15
--- /dev/null
+++ b/results/jobs/20261006-100132-pure-pursuit/gautschi/1/gautschi_launch.py
@@ -0,0 +1,143 @@
+"""Runs on a Gautschi node (stdlib only): episodes from a queue in parallel workers, one contained Apptainer per episode."""
+import argparse
+import json
+import os
+import queue
+import shutil
+import subprocess
+import threading
+import time
+
+RUN = ("source /opt/ros/humble/setup.bash && source /ws/install/setup.bash"
+       " && python3 -m simnode.batch /batch.json /out")
+CUDA_LIB = "/ws/mpc_cuda/libmpc_cuda.so"   # built per stack by runner/gautschi.build_stack for gautschi-gpu
+SAMPLE_S = 15
+STAGGER_S = 0.25   # between worker starts: the dev job's one error was a stack starved in the 96-way start burst
+EPISODE_TIMEOUT_S = 1200   # about 4x the slowest lap; a killed episode has no outcome and is retried by the host
+
+
+def worker_cmd(i, work, out, ep, sif, engine, stack, gpu=None):
+    """Private /tmp, HOME, /dev/shm, IPC, PIDs and loopback per episode, plus a distinct ROS_DOMAIN_ID per worker;
+    gpu (a host CUDA device) adds the driver and the stack's CUDA MPC kernel."""
+    cuda = ["--nv", "--env", f"CUDA_VISIBLE_DEVICES={gpu}", "--env", f"MPC_CUDA_LIB={CUDA_LIB}"] if gpu is not None else []
+    return ["apptainer", "exec", *cuda, "--contain", "--cleanenv", "--ipc", "--pid", "--net", "--network", "none", "--workdir", work,
+            "--env", f"ROS_DOMAIN_ID={i + 1}", "--env", "ROS_HOME=/tmp/ros", "--env", "TMPDIR=/tmp",
+            "--bind", f"{engine}:/opt/sim:ro", "--bind", f"{stack}:/ws:ro", "--bind", f"{out}:/out",
+            "--bind", f"{ep}:/batch.json:ro", sif, "bash", "-lc", RUN]
+
+
+def parse_smi(text):
+    """nvidia-smi 'utilization.gpu, memory.used' csv rows to per-GPU lists."""
+    rows = [[int(v) for v in ln.split(",")] for ln in text.strip().splitlines() if ln.strip()]
+    return {"gpu_util": [r[0] for r in rows], "gpu_mem_mib": [r[1] for r in rows]}
+
+
+def _solver(logdir):
+    """pathfinder's 'MPC solver: ...' and CUDA fallback lines from the episode's ROS logs."""
+    lines = []
+    for dp, _, fns in os.walk(logdir):
+        for fn in fns:
+            try:
+                with open(os.path.join(dp, fn), errors="replace") as f:
+                    lines += [ln.strip() for ln in f if "MPC solver:" in ln or "CUDA MPC unavailable" in ln]
+            except OSError:
+                pass
+    return "\n".join(dict.fromkeys(lines))
+
+
+def main(argv=None):
+    p = argparse.ArgumentParser()
+    for a in ("episodes", "out", "sif", "engine", "stack", "work", "timeline", "done"):
+        p.add_argument("--" + a, required=True)
+    p.add_argument("--workers", type=int, required=True)
+    p.add_argument("--gpus", type=int, default=0)
+    a = p.parse_args(argv)
+    with open(a.episodes) as f:
+        q = queue.Queue()
+        for e in json.load(f):   # the host already ordered them, longest first
+            q.put(e)
+    os.makedirs(a.out, exist_ok=True)
+    lock, t0 = threading.Lock(), time.time()
+    devs = [d for d in os.environ.get("CUDA_VISIBLE_DEVICES", "").split(",") if d][:a.gpus] or [str(n) for n in range(a.gpus)]
+
+    def log(**ev):
+        with lock, open(a.timeline, "a") as f:
+            f.write(json.dumps(dict(ev, t=round(time.time() - t0, 3))) + "\n")
+
+    def worker(i):
+        time.sleep(i * STAGGER_S)
+        while True:
+            try:
+                e = q.get_nowait()
+            except queue.Empty:
+                return
+            key, work = e["key"], os.path.join(a.work, e["key"])
+            stage, ep = os.path.join(work, "stage"), os.path.join(work, "ep.json")
+            os.makedirs(stage)
+            with open(ep, "w") as f:
+                json.dump([e], f)
+            log(ev="start", key=key, worker=i)
+            gpu = devs[i % len(devs)] if devs and e["resolved"].get("recipe", {}).get("sim", {}).get("cuda") else None
+            limit = EPISODE_TIMEOUT_S * max(1, e["resolved"]["scenario"].get("laps", 1))   # per lap: 5-lap episodes run 5x longer
+            try:
+                rc = subprocess.run(worker_cmd(i, work, stage, ep, a.sif, a.engine, a.stack, gpu), stdout=subprocess.DEVNULL,
+                                    stderr=subprocess.DEVNULL, timeout=limit).returncode
+            except subprocess.TimeoutExpired:
+                rc = "timeout"
+            solver = _solver(os.path.join(work, "tmp", "ros", "log"))
+            if solver and os.path.isdir(os.path.join(stage, key)):
+                with open(os.path.join(stage, key, "solver.txt"), "w") as f:
+                    f.write(solver + "\n")
+            if os.path.exists(os.path.join(stage, key, "outcome.json")):
+                tmp, dst = os.path.join(a.out, ".tmp-" + key), os.path.join(a.out, key)
+                shutil.rmtree(tmp, ignore_errors=True)
+                shutil.copytree(os.path.join(stage, key), tmp)
+                shutil.rmtree(dst, ignore_errors=True)
+                os.rename(tmp, dst)   # the host's rsync sees a key only once its directory is complete
+                with lock, open(a.done, "a") as f:
+                    f.write(key + "\n")
+            shutil.rmtree(work, ignore_errors=True)
+            log(ev="end", key=key, worker=i, rc=rc, gpu=gpu,
+                solver=solver.split("MPC solver: ")[-1] if "MPC solver: " in solver else solver or None)
+
+    def sampler(stop):
+        """Job CPU use from its cgroup, as busy cores, every SAMPLE_S."""
+        try:
+            with open("/proc/self/cgroup") as f:
+                path = "/sys/fs/cgroup" + f.read().strip().split(":")[-1] + "/cpu.stat"
+            prev = None
+            while not stop.wait(SAMPLE_S if prev else 0):
+                with open(path) as f:
+                    use = next(int(ln.split()[1]) for ln in f if ln.startswith("usage_usec"))
+                now = time.time()
+                if prev:
+                    log(ev="cpu", busy_cores=round((use - prev[0]) / 1e6 / (now - prev[1]), 2))
+                prev = (use, now)
+        except (OSError, StopIteration, ValueError):
+            pass
+
+    def gpu_sampler(stop):
+        """GPU utilisation and memory of the job's GPUs, every SAMPLE_S."""
+        while not stop.wait(SAMPLE_S):
+            try:
+                p = subprocess.Popen(["nvidia-smi", "--query-gpu=utilization.gpu,memory.used", "--format=csv,noheader,nounits"],
+                                     stdout=subprocess.PIPE, stderr=subprocess.DEVNULL, text=True)
+                log(ev="gpu", **parse_smi(p.communicate(timeout=30)[0]))
+            except Exception:   # no driver or a hung query: skip this sample
+                pass
+
+    cores = len(os.sched_getaffinity(0)) if hasattr(os, "sched_getaffinity") else os.cpu_count()
+    log(ev="launch", workers=a.workers, cores=cores)
+    stop = threading.Event()
+    threads = [threading.Thread(target=worker, args=(i,)) for i in range(a.workers)]
+    samplers = [sampler] + ([gpu_sampler] if a.gpus else [])
+    for t in threads + [threading.Thread(target=f, args=(stop,), daemon=True) for f in samplers]:
+        t.start()
+    for t in threads:
+        t.join()
+    stop.set()
+    log(ev="done")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/results/jobs/20261006-100132-pure-pursuit/gautschi/1/sbatch.sh b/results/jobs/20261006-100132-pure-pursuit/gautschi/1/sbatch.sh
new file mode 100644
index 0000000000000000000000000000000000000000..202356f2c23541bef6fef6b0a8f1dd10813a8317
--- /dev/null
+++ b/results/jobs/20261006-100132-pure-pursuit/gautschi/1/sbatch.sh
@@ -0,0 +1,5 @@
+#!/bin/bash
+#SBATCH -p highmem -A lilly-rob1 -N 1 -n 1 -c 192 --time 86 -J AutoSim-large-pure-pursuit-2 --comment 20261006-100132-pure-pursuit -o AutoSim/jobs/20261006-100132-pure-pursuit/1/slurm-%j.out
+W=/dev/shm/AutoSim-$SLURM_JOB_ID
+trap 'rm -rf "$W"' EXIT
+python3 $HOME/AutoSim/jobs/20261006-100132-pure-pursuit/1/gautschi_launch.py --episodes $HOME/AutoSim/jobs/20261006-100132-pure-pursuit/1/episodes.json --out $HOME/AutoSim/out/20261006-100132-pure-pursuit --sif $HOME/AutoSim/images/AutoSim-99d206f40cb1.sif --engine $HOME/AutoSim/engine/d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f --stack $HOME/AutoSim/stacks/9739f9808d56f172754322c300f08aa20807b22319e73d5d5423ab7f2412fb4d --workers 96 --work $W --timeline $HOME/AutoSim/jobs/20261006-100132-pure-pursuit/1/timeline.jsonl --done $HOME/AutoSim/jobs/20261006-100132-pure-pursuit/1/done.txt
diff --git a/results/jobs/20261006-100132-pure-pursuit/job.json b/results/jobs/20261006-100132-pure-pursuit/job.json
new file mode 100644
index 0000000000000000000000000000000000000000..2808a3aef8dd2c125455984d31a673233c94fc69
--- /dev/null
+++ b/results/jobs/20261006-100132-pure-pursuit/job.json
@@ -0,0 +1,37 @@
+{
+ "id": "20261006-100132-pure-pursuit",
+ "tier": "large",
+ "tier_version": 1,
+ "recipe": {
+  "name": "pure-pursuit",
+  "source": {
+   "repo": "AutonomousKart",
+   "ref": "worktree:AutonomousKart-sim"
+  },
+  "params": {
+   "pathfinder_node": {
+    "planner": "pure_pursuit",
+    "mpc.num_samples": 128
+   }
+  },
+  "notes": "Pure pursuit"
+ },
+ "user": "overnight",
+ "notes": "Pure pursuit",
+ "where": "gautschi",
+ "status": "done",
+ "submitted_at": "2026-10-06T14:01:32.782+00:00",
+ "started_at": "2026-10-06T14:01:34.688+00:00",
+ "finished_at": "2026-10-06T20:07:59.793+00:00",
+ "total": 10692,
+ "done": 10692,
+ "errors": 0,
+ "build_log": null,
+ "workers": 96,
+ "slurm_id": "16883429",
+ "slurm_ids": [
+  "16883429",
+  "16883430"
+ ],
+ "engine_version": "d3d7aaaa9bdfbe38e63169109a8ca928156b53f191894950b6a194219d8c006f"
+}
\ No newline at end of file
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