24. Execution Statistics#

This table contains the latest execution statistics.

Document

Modified

Method

Run Time (s)

Status

ar1_bayes

2026-08-10 03:49

cache

346.33

✅

ar1_turningpts

2026-08-10 03:49

cache

38.4

✅

back_prop

2026-08-10 03:51

cache

95.56

✅

bayes_nonconj

2026-08-10 05:01

cache

4222.09

✅

exchangeable

2026-08-10 05:01

cache

8.41

✅

hoist_failure

2026-08-10 05:02

cache

51.56

✅

imp_sample

2026-08-10 05:06

cache

249.97

✅

intro

2026-08-10 05:06

cache

1.19

✅

likelihood_bayes

2026-08-10 05:07

cache

43.14

✅

likelihood_ratio_process

2026-08-10 05:07

cache

8.86

✅

lln_clt

2026-08-10 05:07

cache

11.24

✅

mix_model

2026-08-10 05:09

cache

68.19

✅

mle

2026-08-10 05:09

cache

5.56

✅

multi_hyper

2026-08-10 05:09

cache

20.31

✅

multivariate_normal

2026-08-10 05:09

cache

4.75

✅

navy_captain

2026-08-10 05:10

cache

28.99

✅

ols

2026-08-10 05:10

cache

9.48

✅

prob_matrix

2026-08-10 05:10

cache

11.16

✅

prob_meaning

2026-08-10 05:11

cache

58.32

✅

rand_resp

2026-08-10 05:11

cache

3.01

✅

status

2026-08-10 05:11

cache

2.64

✅

troubleshooting

2026-08-10 05:06

cache

1.19

✅

util_rand_resp

2026-08-10 05:11

cache

3.11

✅

wald_friedman

2026-08-10 05:11

cache

14.57

✅

zreferences

2026-08-10 05:06

cache

1.19

✅

These lectures are built on linux instances through github actions and amazon web services (aws) to enable access to a gpu. These lectures are built on a p3.2xlarge that has access to 8 vcpu's, a V100 NVIDIA Tesla GPU, and 61 Gb of memory.

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 Aug 10 05:11:32 2026       
+-----------------------------------------------------------------------------------------+
| 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   31C    P0             26W /   70W |     111MiB /  15360MiB |      3%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
                                                                                         
+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|    0   N/A  N/A            7009      C   ...da3/envs/quantecon/bin/python        108MiB |
+-----------------------------------------------------------------------------------------+