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adatune

This is the implementation for paper: AdaTune: Adaptive Tensor Program CompilationMade Efficient (NeurIPS 2020).

algorithms-sedgewick-wayne

Solutions to all the exercises of the Algorithms book by Robert Sedgewick and Kevin Wayne

archbenchsuite

low level kernels to benchmark peak compute, cache bandwidth on various levels, memory bandwidth, and some basic compute routines

assignment2-2018

(Spring 2018) Assignment 2: Graph Executor with TVM

awesome-tensor-compilers

A list of awesome compiler projects and papers for tensor computation and deep learning.

bert4rec

BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

blocking-tutorial

cmssw-dnn

DNN / Tensorflow Interface for CMSSW

compiler2017

A compiler for the course Compiler 2017 at ACM Class, SJTU.

cpufp

A CPU tool for benchmarking the peak of floating points

cuda_hgemm

Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruction.

d2l-tvm

Dive into Deep Learning Compiler

deep-learning-math-kernel-research

effective_transformer

Running BERT without Padding

existing

gpu-benches

collection of benchmarks to measure basic GPU capabilities

habana_custom_kernel

Provides the examples to write and build Habana custom kernels using the HabanaTools

how-to-optimize-gemm

incubator-tvm

Open deep learning compiler stack for cpu, gpu and specialized accelerators

intel-benchmark

keras-mmoe

A Keras implementation of "Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts" (KDD 2018)

ktransformers

A Flexible Framework for Experiencing Cutting-edge LLM Inference Optimizations

lectures

Material for cuda-mode lectures

leetcode_101

LeetCode 101：和你一起你轻松刷题（C++）

llm.c

LLM training in simple, raw C/CUDA

mcbench

Mille Crepe Bench: layer-wise performance analysis for deep learning frameworks.

mixbench

A GPU benchmark tool for evaluating GPUs and CPUs on mixed operational intensity kernels (CUDA, OpenCL, HIP, SYCL, OpenMP)

mlir-examples

a simple end to end example of taking a ML graph (TF2 / PyTorch) and running it on a device [cpu, gpu]

mmperf

MatMul Performance Benchmarks for a Single CPU Core comparing both hand engineered and codegen kernels.

onnxruntime

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