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Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

Zheming Jin

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Tags: Benchmarking, Computer science, CUDA, HIP, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, nVidia H100, oneAPI, Performance, performance portability, SYCL, Tesla A100, Tesla V100

August 14, 2024 by hgpu

LO-SpMM: Low-cost Search for High-performance SpMM Kernels on GPUs

Junqing Lin, Jingwei Sun, Xiaolong Shi, Honghe Zhang, Xianzhi Yu, Xinzhi Wang, Jun Yao, Guangzhong Sun

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Tags: Compilers, Computer science, CUDA, Deep learning, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia GeForce RTX 2080 Ti, Performance, Sparse matrix, Tesla V100

August 4, 2024 by hgpu

Springald: GPU-Accelerated Window-Based Aggregates Over Out-of-Order Data Streams

Gabriele Mencagli, Patrizio Dazzi, Massimo Coppola

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Tags: Computer science, CUDA, DSP, nVidia, nVidia A30, Package, Stream Computing

August 4, 2024 by hgpu

Data-driven Forecasting of Deep Learning Performance on GPUs

Seonho Lee, Amar Phanishayee, Divya Mahajan

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia A100, nVidia H100, nVidia P100, nVidia V100, Performance, PyTorch, Tesla T4

August 4, 2024 by hgpu

Scheduling Deep Learning Jobs in Multi-Tenant GPU Clusters via Wise Resource Sharing

Yizhou Luo, Qiang Wang, Shaohuai Shi, Jiaxin Lai, Shuhan Qi, Jiajia Zhang, Xuan Wang

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Tags: Computer science, CUDA, Deep learning, GPU cluster, nVidia, nVidia GeForce RTX 2080 Ti, OpenMPI, PyTorch, Task scheduling

August 4, 2024 by hgpu

A Comparison of OpenCL, CUDA, and HIP as Compilation Targets for a Functional Array Language

Troels Henriksen

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Tags: AMD Radeon Instinct MI100, ATI, Code generation, Computer science, CUDA, HIP, nVidia, nVidia A100, OpenCL, Package, Programming Languages

July 28, 2024 by hgpu

Bringing Auto-tuning to HIP: Analysis of Tuning Impact and Difficulty on AMD and Nvidia GPUs

Milo Lurati, Stijn Heldens, Alessio Sclocco, Ben van Werkhoven

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Tags: AMD Radeon Instinct MI250X, AMD Radeon Pro W6600, ATI, Computer science, CUDA, HIP, nVidia, nVidia A100, nVidia RTX A4000, Package, Performance, Python

July 28, 2024 by hgpu

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs

Pinxue Zhao, Hailin Zhang, Fangcheng Fu, Xiaonan Nie, Qibin Liu, Fang Yang, Yuanbo Peng, Dian Jiao, Shuaipeng Li, Jinbao Xue, Yangyu Tao, Bin Cui

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Tags: AI, Computer science, CUDA, LLM, Machine learning, NLP, nVidia, nVidia A800

July 28, 2024 by hgpu

RBMD: A molecular dynamics package enabling to simulate 10 million all-atom particles in a single graphics processing unit

Weihang Gao, Teng Zhao, Yongfa Guo, Jiuyang Liang, Huan Liu, Maoying Luo, Zedong Luo, Wei Qin, Yichao Wang, Qi Zhou, Shi Jin, Zhenli Xu

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Tags: Computational Physics, CUDA, Heterogeneous systems, Molecular dynamics, nVidia, nVidia GeForce RTX 4090, Package, Physics, Tesla A100, Tesla V100

July 28, 2024 by hgpu

Optimization of Large-Scale Sparse Matrix-Vector Multiplication on Multi-GPU Systems

Jianhua Gao, Weixing Ji, Yizhuo Wang

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Optimization, Sparse matrix, Tesla V100

July 14, 2024 by hgpu

Harnessing Integrated CPU-GPU System Memory for HPC: a first look into Grace Hopper

Gabin Schieffer, Jacob Wahlgren, Jie Ren, Jennifer Faj, Ivy Peng

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Tags: Computer science, CUDA, HPC, Memory, nVidia, nVidia H100, Performance, Quantum computing

July 14, 2024 by hgpu

Automating Heterogeneous Parallelism in Numerical Differential Equations

Utkarsh

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Tags: AMD RX Vega 64, ATI, Computer science, CUDA, Differential equations, Factorization, Heterogeneous systems, Intel, Intel Arc A770, Julia, Numerical Analysis, nVidia, nVidia Quadro RTX 5000, Package, Tesla V100, Thesis

July 14, 2024 by hgpu

GPU-Smash: Compression abstraction library

A Parallel Compression Pipeline for Improving GPU Virtualization Data Transfers

Owl: Differential-based Side-Channel Leakage Detection for CUDA Applications

pSTL-Bench: Micro-benchmark suite designed to evaluate the scalability and efficiency of parallel C++ STL implementations

Exploring Scalability in C++ Parallel STL Implementations

Noarr Structures

Abstractions for C++ code optimizations in parallel high-performance applications

$3D-fractal-generators$

HiCCL: A hierarchical collective communications library with portable optimizations

HiCCL: A Hierarchical Collective Communication Library

GRAFX: An Open-Source Library for Audio Processing Graphs in PyTorch

In-browser Inference Measurement

Anatomizing Deep Learning Inference in Web Browsers

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high performance computing on graphics processing units: hgpu.org

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

LO-SpMM: Low-cost Search for High-performance SpMM Kernels on GPUs

Springald: GPU-Accelerated Window-Based Aggregates Over Out-of-Order Data Streams

Data-driven Forecasting of Deep Learning Performance on GPUs

Scheduling Deep Learning Jobs in Multi-Tenant GPU Clusters via Wise Resource Sharing

A Comparison of OpenCL, CUDA, and HIP as Compilation Targets for a Functional Array Language

Bringing Auto-tuning to HIP: Analysis of Tuning Impact and Difficulty on AMD and Nvidia GPUs

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs

RBMD: A molecular dynamics package enabling to simulate 10 million all-atom particles in a single graphics processing unit

Optimization of Large-Scale Sparse Matrix-Vector Multiplication on Multi-GPU Systems

Harnessing Integrated CPU-GPU System Memory for HPC: a first look into Grace Hopper

Automating Heterogeneous Parallelism in Numerical Differential Equations

Recent source codes

GPU-Smash: Compression abstraction library

Owl: Differential-based Side-Channel Leakage Detection for CUDA Applications

pSTL-Bench: Micro-benchmark suite designed to evaluate the scalability and efficiency of parallel C++ STL implementations

Noarr Structures

3D-fractal-generators

SyncPerformance

VerCors: a verification toolset for verifying parallel and concurrent software

HiCCL: A hierarchical collective communications library with portable optimizations

GRAFX: An Open-Source Library for Audio Processing Graphs in PyTorch

In-browser Inference Measurement

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