sandeepkumar-skb Goto Github PK

awesome-cv

:page_facing_up: Awesome CV is LaTeX template for your outstanding job application

axlearn

An Extensible Deep Learning Library

backend

Common source, scripts and utilities for creating Triton backends.

badwolf

A Vim color scheme.

code-samples

Source code examples from the Parallel Forall Blog

cs344

Introduction to Parallel Programming class code

fast_upsampling

fasterai

FasterAI: A repository for making smaller and faster models with the FastAI library.

llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

llm_from_scratch

mpitutorial

MPI programming lessons in C and executable code examples

nanogpt

The simplest, fastest repository for training/finetuning medium-sized GPTs.

nccl

Optimized primitives for collective multi-GPU communication

onnxruntime

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

openai-triton-kernels

OpenAI Triton Kernels

picogpt

An unnecessarily tiny implementation of GPT-2 in NumPy.

professional-programming

A collection of learning resources for curious software engineers

python_backend

Triton backend that enables pre-process, post-processing and other logic to be implemented in Python.

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch_custom_op

End to End steps for adding custom ops in PyTorch.

pytorch_extension

Pytorch extension examples

pytorch_multistreaming

PyTorch CUDA multistreaming in Python and CPP(TorchScript)

pytorch_trt_experiments

raytracinginoneweekendincuda

The code for the ebook Ray Tracing in One Weekend by Peter Shirley translated to CUDA by Roger Allen. This work is in the public domain.

sandeepkumar-skb.github.io

My personal website

server

The Triton Inference Server provides an optimized cloud and edge inferencing solution.

tensorrt_python_samples

tinyllama

The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.

toma

Helps you write algorithms in PyTorch that adapt to the available (CUDA) memory

torch2trt

An easy to use PyTorch to TensorRT converter