malfet

import torch
import torch.nn.functional as F

def to_float8(x, dtype=torch.float8_e4m3fn):
    finfo = torch.finfo(dtype)
    # Calculate the scale as dtype max divided by absmax
    scale = finfo.max / x.abs().max().clamp(min=1e-12)
    # scale and clamp the tensor to bring it to
    # the representative range of float8 data type
    # (as default cast is unsaturated)

mingfeima

Part I: Memory Formats and Channels Last Optimization

(Training material on pytorch CPU performance optimization)

• Part II: Parallelization Techniques
• Part III: Vectorization Techniques
• Part IV: BFloat16 Kernel Optimization

Chinese version for this chapter, link.

mcarilli

# This isn't supposed to run as a bash script, i named it with ".sh" for syntax highlighting.

# https://developer.nvidia.com/nsight-systems
# https://docs.nvidia.com/nsight-systems/profiling/index.html

# My preferred nsys (command line executable used to create profiles) commands
#
# In your script, write
# torch.cuda.nvtx.range_push("region name")
# ...

gonzaloplaza

#!/bin/bash
# Install docker
apt-get update
apt-get install -y cloud-utils apt-transport-https ca-certificates curl software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
add-apt-repository \
   "deb [arch=amd64] https://download.docker.com/linux/ubuntu \
   $(lsb_release -cs) \
   stable"
apt-get update

barosl

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

int addi(int a, int b) {
    return a + b;
}

char *adds(char *a, char *b) {
    char *res = malloc(strlen(a) + strlen(b) + 1);