diff --git a/.gitattributes b/.gitattributes
index 176b812f572a331a0dd28d60e5fb060f3d8d7485..108d74afd6d23781310205b7d20a386a5a048393 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -59,3 +59,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.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
+results/jobs/20261006-203943-pure-pursuit/episodes.jsonl filter=lfs diff=lfs merge=lfs -text
diff --git a/results/index/episodes.jsonl b/results/index/episodes.jsonl
index 618e5cdaa5c2c6405a17818b7be1fbbdd34a021f..adf559940d4fdcc117c8dd62be8da74eab8499a6 100644
--- a/results/index/episodes.jsonl
+++ b/results/index/episodes.jsonl
@@ -11502,3 +11502,10695 @@
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diff --git a/results/jobs/20261006-203943-pure-pursuit/breakdown.json b/results/jobs/20261006-203943-pure-pursuit/breakdown.json
new file mode 100644
index 0000000000000000000000000000000000000000..d5f7af71856bd1a9ea881cb0dff386fcad7fb9d5
--- /dev/null
+++ b/results/jobs/20261006-203943-pure-pursuit/breakdown.json
@@ -0,0 +1,84260 @@
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+ }
+}
\ No newline at end of file
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diff --git a/results/jobs/20261006-203943-pure-pursuit/gautschi/0/done.txt b/results/jobs/20261006-203943-pure-pursuit/gautschi/0/done.txt
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diff --git a/results/jobs/20261006-203943-pure-pursuit/gautschi/0/episodes.json b/results/jobs/20261006-203943-pure-pursuit/gautschi/0/episodes.json
new file mode 100644
index 0000000000000000000000000000000000000000..cb4ce4d0f32fd47a3d18bcd673483823d8c006f8
--- /dev/null
+++ b/results/jobs/20261006-203943-pure-pursuit/gautschi/0/episodes.json
@@ -0,0 +1 @@
+[{"key": "11fcc861055fd847411dbb6ee6602b6f8088686024fe464226134a66c32d6a7f", "resolved": {"kart": {"name": "kart1", "chrono_dir": "chrono/kart", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 49.98, "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": 2.0, "latency_ms": 150.0, "rate_hz": 20.0, "float_dwell_scale": 3.0, "outages": true, "wrong_fix": true, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 1.0, "dlpf_hz": 0}, "wheel": {"white_mps": 0.08, "scale_error": 0.033, "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_high_steer_high", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "81dde8e4b2839f17deb71b563f489f8754e1fe4f561790f0fdc69e0bd1ec783f"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit, fixed motor noise + ghost, steering high 50 deg/s"}, "scenario": {"type": "lap", "line": "center", "laps": 5}, "seed": 2271313913, "tier": "large", "engine_version": "7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae"}}, {"key": "6aedc9a8f45c89c6113970438f27d625f5bd12f075b67641eec25c4bda2314b0", "resolved": {"kart": {"name": "kart3", "chrono_dir": "chrono/kart3", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 50.693999999999996, "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": 2.0, "latency_ms": 150.0, "rate_hz": 20.0, "float_dwell_scale": 3.0, "outages": true, "wrong_fix": true, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 1.0, "dlpf_hz": 0}, "wheel": {"white_mps": 0.08, "scale_error": 0.033, "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_high_steer_high", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "81dde8e4b2839f17deb71b563f489f8754e1fe4f561790f0fdc69e0bd1ec783f"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit, fixed motor noise + ghost, steering high 50 deg/s"}, "scenario": {"type": "lap", "line": "center", "laps": 5}, "seed": 3011476007, "tier": "large", "engine_version": "7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae"}}, {"key": "408bd6347ddd93e53bb62964560c6b874ebda866d5adb894ae45dcb6d6e4dc9b", "resolved": {"kart": {"name": "kart2", "chrono_dir": "chrono/kart2", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 49.98, "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": 2.0, "latency_ms": 150.0, "rate_hz": 20.0, "float_dwell_scale": 3.0, "outages": true, "wrong_fix": true, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 1.0, "dlpf_hz": 0}, "wheel": {"white_mps": 0.08, "scale_error": 0.033, "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_high_steer_high", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "81dde8e4b2839f17deb71b563f489f8754e1fe4f561790f0fdc69e0bd1ec783f"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit, fixed motor noise + ghost, steering high 50 deg/s"}, "scenario": {"type": "lap", "line": "line1", "laps": 5}, "seed": 3417932256, "tier": "large", "engine_version": "7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae"}}, {"key": "ac39feaa162cf86be2425f6533f546865852a15c6802bc3cb21eba40d3ae930a", "resolved": {"kart": {"name": "kart1", "chrono_dir": "chrono/kart", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 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"source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "81dde8e4b2839f17deb71b563f489f8754e1fe4f561790f0fdc69e0bd1ec783f"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit, fixed motor noise + ghost, steering high 50 deg/s"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 970488497, "tier": "large", "engine_version": "7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae"}}]
\ No newline at end of file
diff --git a/results/jobs/20261006-203943-pure-pursuit/gautschi/0/gautschi_launch.py b/results/jobs/20261006-203943-pure-pursuit/gautschi/0/gautschi_launch.py
new file mode 100644
index 0000000000000000000000000000000000000000..bf8e0fad5f2b6ef416b2f1d3b27679a56f888d15
--- /dev/null
+++ b/results/jobs/20261006-203943-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/20261006-203943-pure-pursuit/gautschi/0/sbatch.sh b/results/jobs/20261006-203943-pure-pursuit/gautschi/0/sbatch.sh
new file mode 100644
index 0000000000000000000000000000000000000000..bd883849d7f74819522c16a44961a00ac0b23fad
--- /dev/null
+++ b/results/jobs/20261006-203943-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 20261006-203943-pure-pursuit -o AutoSim/jobs/20261006-203943-pure-pursuit/0/slurm-%j.out
+W=/dev/shm/AutoSim-$SLURM_JOB_ID
+trap 'rm -rf "$W"' EXIT
+python3 $HOME/AutoSim/jobs/20261006-203943-pure-pursuit/0/gautschi_launch.py --episodes $HOME/AutoSim/jobs/20261006-203943-pure-pursuit/0/episodes.json --out /scratch/gautschi/manors/AutoSim/out/20261006-203943-pure-pursuit --sif $HOME/AutoSim/images/AutoSim-99d206f40cb1.sif --engine $HOME/AutoSim/engine/7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae --stack $HOME/AutoSim/stacks/81dde8e4b2839f17deb71b563f489f8754e1fe4f561790f0fdc69e0bd1ec783f --workers 96 --work $W --timeline $HOME/AutoSim/jobs/20261006-203943-pure-pursuit/0/timeline.jsonl --done $HOME/AutoSim/jobs/20261006-203943-pure-pursuit/0/done.txt
diff --git a/results/jobs/20261006-203943-pure-pursuit/gautschi/1/done.txt b/results/jobs/20261006-203943-pure-pursuit/gautschi/1/done.txt
new file mode 100644
index 0000000000000000000000000000000000000000..099e8376e2c82299a4319f7e6cd1ac9ac358e058
--- /dev/null
+++ b/results/jobs/20261006-203943-pure-pursuit/gautschi/1/done.txt
@@ -0,0 +1,5346 @@
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diff --git a/results/jobs/20261006-203943-pure-pursuit/gautschi/1/episodes.json b/results/jobs/20261006-203943-pure-pursuit/gautschi/1/episodes.json
new file mode 100644
index 0000000000000000000000000000000000000000..4a1eab879d406d0ccf378b464f179f5361ac36dc
--- /dev/null
+++ b/results/jobs/20261006-203943-pure-pursuit/gautschi/1/episodes.json
@@ -0,0 +1 @@
+[{"key": "b0c795e9c65b163c0bae5eb17fcd1a64eab0d6dffa99e08c4b167b2792779dfb", "resolved": {"kart": {"name": "kart2", "chrono_dir": "chrono/kart2", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 49.98, "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": 2.0, "latency_ms": 150.0, "rate_hz": 20.0, "float_dwell_scale": 3.0, "outages": true, "wrong_fix": true, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 1.0, "dlpf_hz": 0}, "wheel": {"white_mps": 0.08, "scale_error": 0.033, "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_high_steer_high", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "81dde8e4b2839f17deb71b563f489f8754e1fe4f561790f0fdc69e0bd1ec783f"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit, fixed motor noise + ghost, steering high 50 deg/s"}, "scenario": {"type": "lap", "line": "center", "laps": 5}, "seed": 2495023460, "tier": "large", "engine_version": "7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae"}}, {"key": "8c71548051fc47638db938db66594898f3ba8cfdc43b5326784c68cdaed0f52b", "resolved": {"kart": {"name": "kart1", "chrono_dir": "chrono/kart", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 49.98, "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": 2.0, "latency_ms": 150.0, "rate_hz": 20.0, "float_dwell_scale": 3.0, "outages": true, "wrong_fix": true, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 1.0, "dlpf_hz": 0}, "wheel": {"white_mps": 0.08, "scale_error": 0.033, "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_high_steer_high", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", "tree": "81dde8e4b2839f17deb71b563f489f8754e1fe4f561790f0fdc69e0bd1ec783f"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit, fixed motor noise + ghost, steering high 50 deg/s"}, "scenario": {"type": "lap", "line": "line1", "laps": 5}, "seed": 474270773, "tier": "large", "engine_version": "7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae"}}, {"key": "0d9aec0305d7c5c6b10bc4927ff8d5ba9fe3fe40456bf65a7a639955069c6799", "resolved": {"kart": {"name": "kart3", "chrono_dir": "chrono/kart3", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 50.693999999999996, "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": 2.0, "latency_ms": 150.0, "rate_hz": 20.0, "float_dwell_scale": 3.0, "outages": true, "wrong_fix": true, "heading_source": "vtg"}, "imu": {"enabled": true, "vibration_scale": 1.0, "dlpf_hz": 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{"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 49.98, "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": "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_high", "recipe": {"name": "pure-pursuit", "source": {"repo": "AutonomousKart", "ref": "worktree:/Users/shay/PycharmProjects/AutonomousKart-sim", 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"mpc.num_samples": 128}}, "notes": "Pure pursuit, fixed motor noise + ghost, steering high 50 deg/s"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 4249680720, "tier": "large", "engine_version": "7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae"}}, {"key": "cc2bc19bff2aeb9bf1c86f0f4654d517db06f5e9fb32012c460b40a0ca7c28bb", "resolved": {"kart": {"name": "kart1", "chrono_dir": "chrono/kart", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 49.98, "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, 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"resolved": {"kart": {"name": "kart3", "chrono_dir": "chrono/kart3", "tyres": {"grip": 1.0}, "frame": {"torsion_scale": 1.0}, "steering_motor": {"rate_dps": 50.693999999999996, "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": 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{"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": "81dde8e4b2839f17deb71b563f489f8754e1fe4f561790f0fdc69e0bd1ec783f"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit, fixed motor noise + ghost, steering high 50 deg/s"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 3186302859, "tier": "large", "engine_version": "7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae"}}, {"key": "3a0659a2fccdf131411a1a6dbb7ad57707e95aad8c3e6bcfb554dd3df0f93151", "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": "81dde8e4b2839f17deb71b563f489f8754e1fe4f561790f0fdc69e0bd1ec783f"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit, fixed motor noise + ghost, steering high 50 deg/s"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 362170483, "tier": "large", "engine_version": "7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae"}}, {"key": "949e6e16b272ddc621742e6a192db0959a4bc6f96f7a7809b85b552e6ebd1a3e", "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": "81dde8e4b2839f17deb71b563f489f8754e1fe4f561790f0fdc69e0bd1ec783f"}, "params": {"pathfinder_node": {"planner": "pure_pursuit", "mpc.num_samples": 128}}, "notes": "Pure pursuit, fixed motor noise + ghost, steering high 50 deg/s"}, "scenario": {"type": "clip", "clip_id": "20261003_195721_auto_00019"}, "seed": 3171405895, "tier": "large", "engine_version": "7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae"}}]
\ No newline at end of file
diff --git a/results/jobs/20261006-203943-pure-pursuit/gautschi/1/gautschi_launch.py b/results/jobs/20261006-203943-pure-pursuit/gautschi/1/gautschi_launch.py
new file mode 100644
index 0000000000000000000000000000000000000000..bf8e0fad5f2b6ef416b2f1d3b27679a56f888d15
--- /dev/null
+++ b/results/jobs/20261006-203943-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/20261006-203943-pure-pursuit/gautschi/1/sbatch.sh b/results/jobs/20261006-203943-pure-pursuit/gautschi/1/sbatch.sh
new file mode 100644
index 0000000000000000000000000000000000000000..38995bb031190061013f273fccb6be56836f9eff
--- /dev/null
+++ b/results/jobs/20261006-203943-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 20261006-203943-pure-pursuit -o AutoSim/jobs/20261006-203943-pure-pursuit/1/slurm-%j.out
+W=/dev/shm/AutoSim-$SLURM_JOB_ID
+trap 'rm -rf "$W"' EXIT
+python3 $HOME/AutoSim/jobs/20261006-203943-pure-pursuit/1/gautschi_launch.py --episodes $HOME/AutoSim/jobs/20261006-203943-pure-pursuit/1/episodes.json --out /scratch/gautschi/manors/AutoSim/out/20261006-203943-pure-pursuit --sif $HOME/AutoSim/images/AutoSim-99d206f40cb1.sif --engine $HOME/AutoSim/engine/7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae --stack $HOME/AutoSim/stacks/81dde8e4b2839f17deb71b563f489f8754e1fe4f561790f0fdc69e0bd1ec783f --workers 96 --work $W --timeline $HOME/AutoSim/jobs/20261006-203943-pure-pursuit/1/timeline.jsonl --done $HOME/AutoSim/jobs/20261006-203943-pure-pursuit/1/done.txt
diff --git a/results/jobs/20261006-203943-pure-pursuit/job.json b/results/jobs/20261006-203943-pure-pursuit/job.json
new file mode 100644
index 0000000000000000000000000000000000000000..ca71b8ad963bffd65d8628318e936f4a1a28e974
--- /dev/null
+++ b/results/jobs/20261006-203943-pure-pursuit/job.json
@@ -0,0 +1,37 @@
+{
+ "id": "20261006-203943-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, fixed motor noise + ghost, steering high 50 deg/s"
+ },
+ "user": "overnight",
+ "notes": "Pure pursuit, fixed motor noise + ghost, steering high 50 deg/s",
+ "where": "gautschi",
+ "status": "done",
+ "submitted_at": "2026-10-07T00:39:43.054+00:00",
+ "started_at": "2026-10-07T00:39:44.777+00:00",
+ "finished_at": "2026-10-07T02:21:02.291+00:00",
+ "total": 10692,
+ "done": 10692,
+ "errors": 0,
+ "build_log": null,
+ "workers": 96,
+ "slurm_id": "16888902",
+ "slurm_ids": [
+  "16888902",
+  "16888903"
+ ],
+ "engine_version": "7c23fecc8b44bf60ed57bd3279be7b1bb237d3d2d4f0868bef856ffbde4092ae"
+}
\ No newline at end of file
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