顯示具有 spec 標籤的文章。 顯示所有文章
顯示具有 spec 標籤的文章。 顯示所有文章

Virtual Machine Spec for Google Colab Environment

Google Colab提供最多12小時連線的Jupyter Notebook開發環境,其2018年底層的虛擬機實測規格如下:

CPU: Intel(R) Xeon(R) TwinCore @ 2.20GHz x 2

Memory: 13GB

Drive: 347GB

GPU: Tesla K80 with 4992 cores at 556MHz + 11GB Memory

OS: Ubuntu 18.04.1 LTS

Time Limit: 12 hours

規格實測的python指令如下:

# https://stackoverflow.com/questions/48750199/google-colaboratory-misleading-information-about-its-gpu-only-5-ram-available
# memory footprint support libraries/code
!ln -sf /opt/bin/nvidia-smi /usr/bin/nvidia-smi
!pip install gputil
!pip install psutil
!pip install humanize
import psutil
import humanize
import os
import GPUtil as GPU
GPUs = GPU.getGPUs()
# XXX: only one GPU on Colab and isn? guaranteed
gpu = GPUs[0]
def printm():
 process = psutil.Process(os.getpid())
 print("Gen RAM Free: " + humanize.naturalsize( psutil.virtual_memory().available ), " | Proc size: " + humanize.naturalsize( process.memory_info().rss))
 print("GPU RAM Free: {0:.0f}MB | Used: {1:.0f}MB | Util {2:3.0f}% | Total {3:.0f}MB".format(gpu.memoryFree, gpu.memoryUsed, gpu.memoryUtil*100, gpu.memoryTotal))
printm()

!df
!cat /etc/issue
!nvidia-smi
!nvidia-smi -L

!cat /proc/cpuinfo
!cat /proc/meminfo

how to call Java classes in a web page by cheerpj

🚀 在瀏覽器中直接執行 Java:CheerpJ v3 實作指南 長期以來,Java Applets 因為安全性與插件問題早已退出歷史舞台。但隨著 WebAssembly (Wasm) 技術的成熟,現在網頁安裝如下 CheerpJ v3 套件庫,就可以在瀏覽器中直接呼叫 ...

總網頁瀏覽量