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alshedivat-al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

antares

Antares: an automatic engine for multi-platform kernel generation and optimization. Supporting CPU, CUDA, ROCm, DirectX12, GraphCore, SYCL for CPU/GPU, OpenCL for AMD/NVIDIA, Android CPU/GPU backends.

apple-opencl-fft

A crude Linux port of the Apple OpenCL FFT

blis

BLAS-like Library Instantiation Software Framework

carol-fi

Fault Injector

clgpu

cm-compiler

cpu_gemm_opt

how to design cpu gemm on x86 with avx256, that can beat openblas.

cryptonets

CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.

cufhe

CUDA-accelerated Fully Homomorphic Encryption Library

cutlass

CUDA Templates for Linear Algebra Subroutines

effective_transformer

Running BERT without Padding

esecurity

MSc Module

fastertransformer

Transformer related optimization, including BERT, GPT

fft_simd

A simple demo shows how to use the SIMD,Single Instruction Multiple Data, to optimize and accelerate the FFT algorithm.

ftblas

A high-performance BLAS implementation with online fault tolerance.

gcngemm

Optimized half precision gemm assembly kernels (deprecated due to ROCm)

heaan

helib

HElib is an open-source software library that implements homomorphic encryption. It supports the BGV scheme with bootstrapping and the Approximate Number CKKS scheme. HElib also includes optimizations for efficient homomorphic evaluation, focusing on effective use of ciphertext packing techniques and on the Gentry-Halevi-Smart optimizations.

hexl

Intel:registered: Homomorphic Encryption Acceleration Library accelerates modular arithmetic operations used in homomorphic encryption

icc-travis

Script to help install Intel C/C++ Compiler on Travis CI.

intel-graphics-compiler

java-program-profiling

lab2-f17

CS153 lab2

libfacedetection

An open source library for face detection in images. The face detection speed can reach 1000FPS.

llvm-test-suite

math-atlas

Automatically Tuned Linear Algebra Software (ATLAS)

maxas

Assembler for NVIDIA Maxwell architecture

memory-bandwidth-demo

An attempt at achieving the theoretical best memory bandwidth of my machine.

ml2021-spring

**Official** 李宏毅 (Hung-yi Lee) 機器學習 Machine Learning 2021 Spring