26. Execution Statistics#
This table contains the latest execution statistics.
Document |
Modified |
Method |
Run Time (s) |
Status |
---|---|---|---|---|
2025-05-19 03:32 |
cache |
68.83 |
✅ |
|
2025-05-19 03:33 |
cache |
22.52 |
✅ |
|
2025-05-19 03:33 |
cache |
13.19 |
✅ |
|
2025-05-19 03:33 |
cache |
24.88 |
✅ |
|
2025-05-19 03:36 |
cache |
143.13 |
✅ |
|
2025-05-19 03:36 |
cache |
1.18 |
✅ |
|
2025-05-19 03:36 |
cache |
9.7 |
✅ |
|
2025-05-19 04:12 |
cache |
2142.59 |
✅ |
|
2025-05-19 04:12 |
cache |
41.96 |
✅ |
|
2025-05-19 04:14 |
cache |
97.76 |
✅ |
|
2025-05-19 04:14 |
cache |
10.27 |
✅ |
|
2025-05-19 04:14 |
cache |
28.08 |
✅ |
|
2025-05-19 04:15 |
cache |
15.29 |
✅ |
|
2025-05-19 04:15 |
cache |
20.16 |
✅ |
|
2025-05-19 04:15 |
cache |
11.93 |
✅ |
|
2025-05-19 04:16 |
cache |
15.67 |
✅ |
|
2025-05-19 04:19 |
cache |
186.86 |
✅ |
|
2025-05-19 04:19 |
cache |
22.82 |
✅ |
|
2025-05-19 04:20 |
cache |
50.87 |
✅ |
|
2025-05-19 04:20 |
cache |
21.02 |
✅ |
|
2025-05-20 05:59 |
cache |
34.54 |
✅ |
|
2025-05-19 04:21 |
cache |
4.46 |
✅ |
|
2025-05-19 04:21 |
cache |
2.47 |
✅ |
|
2025-05-19 03:36 |
cache |
1.18 |
✅ |
|
2025-05-19 04:23 |
cache |
158.44 |
✅ |
|
2025-05-19 03:36 |
cache |
1.18 |
✅ |
These lectures are built on linux
instances through github actions
that has
access to a gpu
. These lectures make use of the nvidia T4
card.
You can check the backend used by JAX using:
import jax
# Check if JAX is using GPU
print(f"JAX backend: {jax.devices()[0].platform}")
JAX backend: gpu
and the hardware we are running on:
!nvidia-smi
/home/runner/miniconda3/envs/quantecon/lib/python3.12/pty.py:95: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.
pid, fd = os.forkpty()
Mon May 19 04:21:15 2025
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 575.51.03 Driver Version: 575.51.03 CUDA Version: 12.9 |
|-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 Tesla T4 Off | 00000000:00:1E.0 Off | 0 |
| N/A 34C P0 32W / 70W | 109MiB / 15360MiB | 1% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| 0 N/A N/A 8505 C ...da3/envs/quantecon/bin/python 106MiB |
+-----------------------------------------------------------------------------------------+