21. Execution Statistics#

This table contains the latest execution statistics.

Document

Modified

Method

Run Time (s)

Status

aiyagari_jax

2024-04-01 17:20

cache

65.97

✅

arellano

2024-04-01 17:21

cache

30.03

✅

cake_eating_numerical

2024-04-01 17:21

cache

21.03

✅

ifp_egm

2024-04-01 17:24

cache

180.97

✅

intro

2024-04-01 17:24

cache

1.16

✅

inventory_dynamics

2024-04-01 17:25

cache

72.43

✅

inventory_ssd

2024-04-01 17:50

cache

1494.46

✅

jax_intro

2024-04-01 17:50

cache

26.97

✅

kesten_processes

2024-04-01 17:51

cache

20.98

✅

lucas_model

2024-04-01 17:51

cache

20.78

✅

markov_asset

2024-04-01 17:51

cache

18.81

✅

mle

2024-04-01 17:52

cache

16.02

✅

newtons_method

2024-04-01 17:54

cache

160.49

✅

opt_invest

2024-04-01 22:27

cache

23.67

✅

opt_savings_1

2024-04-01 17:55

cache

38.21

✅

opt_savings_2

2024-04-01 22:27

cache

17.69

✅

short_path

2024-04-01 17:56

cache

6.89

✅

status

2024-04-01 17:56

cache

4.03

✅

troubleshooting

2024-04-01 17:24

cache

1.16

✅

wealth_dynamics

2024-04-01 22:29

cache

108.05

✅

zreferences

2024-04-01 17:24

cache

1.16

✅

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

/opt/conda/envs/quantecon/lib/python3.11/pty.py:89: 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 Apr  1 17:56:24 2024       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.182.03   Driver Version: 470.182.03   CUDA Version: 12.3     |
|-------------------------------+----------------------+----------------------+
| 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 V100-SXM2...  Off  | 00000000:00:1E.0 Off |                    0 |
| N/A   28C    P0    37W / 300W |    310MiB / 16160MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
+-----------------------------------------------------------------------------+