joeking11829

#!/bin/bash

# ssh-cipher-benchmark.sh - Assesses speed of SSH encryption between specific hosts.
# Usage:
# ssh-cipher-benchmark.sh <remotehost> [ciphers]
# Default ciphers: all we can find...
#
# Note: In some cases, the first cipher tested runs faster than the others, regardless of order.
# Cause of this is not known, but changing the order of testing shows it to be true.  Run the
# first one twice if you suspect this.  Perhaps it is due to buffering?

joeking11829

The fastest remote directory rsync over ssh archival I can muster (40MB/s over 1gb NICs)

This creates an archive that does the following:

rsync (Everyone seems to like -z, but it is much slower for me)

• a: archive mode - rescursive, preserves owner, preserves permissions, preserves modification times, preserves group, copies symlinks as symlinks, preserves device files.
• H: preserves hard-links
• A: preserves ACLs

joeking11829

#!/usr/bin/env python
# -*- coding: utf-8 -*-
from argparse import ArgumentParser

import torch
import torch.distributed as dist
from torch.nn.parallel import DistributedDataParallel as DDP
from torch.utils.data import DataLoader, Dataset
from torch.utils.data.distributed import DistributedSampler
from transformers import BertForMaskedLM

joeking11829

注意：本文内容适用于 Tmux 2.3 及以上的版本，但是绝大部分的特性低版本也都适用，鼠标支持、VI 模式、插件管理在低版本可能会与本文不兼容。

Tmux 快捷键 & 速查表

启动新会话：

tmux [new -s 会话名 -n 窗口名]

恢复会话：

joeking11829

create /etc/lightdm/lightdm.conf.d/20-ubuntu.conf as follows:

Add to the new file:
[SeatDefaults]
greeter-setup-script=/usr/bin/synergyc --daemon [server address]
user-session=Ubuntu

Set the proper permissions:
$ sudo chmod 600 20-lubuntu.conf 
$ ls 20-lubuntu.conf 

joeking11829

Convert Binary Data to OpenCV Image Format

在影像處理時，常常會讀取影像資料(binary data)後轉成影像格式(cv::Mat)，在進行影像操作。

那我們如何轉成可用的OpenCV影像格式呢?

首先讀取檔案後得到binary data，在進行解碼轉成cv::Mat。

當然如果單純讀檔後轉成OpenCV影像格式，OpenCV是有提供cv::imread這個API可以使用。

joeking11829

#!/bin/sh
# Set CPU to full performance on NVIDIA Jetson TK1 Development Kit
if [ $(id -u) != 0 ]; then
   echo "This script requires root permissions"
   echo "$ sudo "$0""
   exit
fi
 
# To obtain full performance on the CPU (eg: for performance measurements or benchmarking or when you don't care about power draw), you can disable CPU scaling and force the 4 main CPU cores to always run at max performance until reboot:

joeking11829

#!/bin/sh
# Install cuDNN V2 on NVIDIA Jetson TK1
# Register as a NVIDIA developer and download the cuDNN package
# Package is named cudnn-6.5-linux-ARMv7-V2.tgz
# This script and the cuDNN package should be in the same directory, usually ~/Downloads
# This script places the library and include files for cudnn in the CUDA 6.5 directories
# Make sure this is executing as root
if [ $(id -u) != 0 ]; then
  echo "This script requires root permissions"
  echo "$ sudo "$0""

joeking11829

#!/bin/sh
# Install and compile Caffe on NVIDIA Jetson TK1 Development Kit
sudo add-apt-repository universe
sudo apt-get update
sudo apt-get install libprotobuf-dev protobuf-compiler gfortran \
libboost-dev cmake libleveldb-dev libsnappy-dev \
libboost-thread-dev libboost-system-dev \
libatlas-base-dev libhdf5-serial-dev libgflags-dev \
libgoogle-glog-dev liblmdb-dev -y

joeking11829

Caffe + Ubuntu 12.04 64bit + CUDA 6.5 配置说明

本步骤能实现用Intel核芯显卡来进行显示， 用NVIDIA GPU进行计算。

1. 安装开发所需的依赖包

安装开发所需要的一些基本包

sudo apt-get install build-essential
sudo apt-get install vim cmake git
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev