high performance computing on graphics processing units: hgpu.org

Deepak Narayanan, Mohammad Shoeybi, Jared Casper, Patrick LeGresley, Mostofa Patwary, Vijay Korthikanti, Dmitri Vainbrand, Prethvi Kashinkunti, Julie Bernauer, Bryan Catanzaro, Amar Phanishayee, Matei Zaharia

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Tags: Computer science, CUDA, Data parallelism, Deep learning, GPU cluster, NLP, nVidia, nVidia DGX-A100, Package

April 18, 2021 by hgpu

A Hybrid Parallelization Approach for Distributed and Scalable Deep Learning

Samson B. Akintoye, Liangxiu Han, Xin Zhang, Haoming Chen, Daoqiang Zhang

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Tags: Computer science, CUDA, Data parallelism, Deep learning, Neural networks, nVidia, Tesla V100

April 18, 2021 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

NPBench: A Benchmarking Suite for High-Performance NumPy

A fluid simulation system based on the MPS method

DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning

Performance analysis and optimization of highly diverging algorithms on GPUs

Easy and Efficient Transformer: Scalable Inference Solution For large NLP mode

Ripple: Simplified Large-Scale Computation on Heterogeneous Architectures with Polymorphic Data Layout

CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU

Performance Analysis and Optimization Opportunities for NVIDIA Automotive GPUs

SLATE port to AMD and Intel platforms

Under the Hood of SYCL – An Initial Performance Analysis With an Unstructured-mesh CFD Application

Efficient Large-Scale Language Model Training on GPU Clusters

A Hybrid Parallelization Approach for Distributed and Scalable Deep Learning

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR