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Accelerating JPEG Decompression on GPUs

André Weißenberger, Bertil Schmidt

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Tags: Compression, CUDA, Image processing, nVidia, nVidia A100

November 21, 2021 by hgpu

QGTC: Accelerating Quantized GNN via GPU Tensor Core

Yuke Wang, Boyuan Feng, Yufei Ding

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce RTX 3090, TPU

November 21, 2021 by hgpu

General purpose lattice QCD code set Bridge++ 2.0 for high performance computing

Yutaro Akahoshi, Sinya Aoki, Tatsumi Aoyama, Issaku Kanamori, Kazuyuki Kanaya, Hideo Matsufuru, Yusuke Namekawa, Hidekatsu Nemura, Yusuke Taniguchi

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Tags: GPU cluster, HEP, High Energy Physics - Lattice, Numerical simulation, nVidia, OpenACC, Package, Physics, QCD, Tesla V100

November 14, 2021 by hgpu

Performance Optimisations for Heterogeneous Managed Runtime Systems

Michail Papadimitriou

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Tags: Computer science, FPGA, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX 1650, OpenCL, Performance, Thesis

November 14, 2021 by hgpu

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

Zane Fink, Simeng Liu, Jaemin Choi, Matthias Diener, Laxmikant V. Kale

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Tags: Benchmarking, Computer science, CUDA, Distributed computing, HPC, Machine learning, MPI, nVidia, Package, Performance, Python, Tesla V100

November 14, 2021 by hgpu

Collage: Automated Integration of Deep Learning Backends

Byungsoo Jeon, Sunghyun Park, Peiyuan Liao, Sheng Xu, Tianqi Chen, Zhihao Jia

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce RTX 2070, Tesla V100

November 7, 2021 by hgpu

iGUARD: In-GPU Advanced Race Detection

Aditya K Kamath, Arkaprava Basu

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Tags: Computer science, CUDA, nVidia, nVidia Titan RTX, Package, Performance

November 7, 2021 by hgpu

Principles towards Real-Time Simulation of Material Point Method on Modern GPUs

Yun Fei, Yuhan Huang, Ming Gao

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Tags: Computer science, CUDA, Graphics, nVidia, nVidia DGX-1, Physics-based simulation, Tesla V100

November 7, 2021 by hgpu

Improving Performance and Energy Efficiency of GPUs through Locality Analysis

Devashree Tripathy

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX Titan V, nVidia GeForce GTX Titan X, Performance, PTX, Thesis

October 31, 2021 by hgpu

Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training

Zhengda Bian, Hongxin Liu, Boxiang Wang, Haichen Huang, Yongbin Li, Chuanrui Wang, Fan Cui, Yang You

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Tags: Computer science, CUDA, Data parallelism, Deep learning, nVidia, Package, Tesla P100

October 31, 2021 by hgpu

Mixed precision in Graphics Processing Unit

Quentin Gallouédec

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Tags: Computer science, Machine learning, Mixed precision, Neural networks, nVidia, Tesla V100

October 31, 2021 by hgpu

TorchAudio: Building Blocks for Audio and Speech Processing

Yao-Yuan Yang, Moto Hira, Zhaoheng Ni, Anjali Chourdia, Artyom Astafurov, Caroline Chen, Ching-Feng Yeh, Christian Puhrsch, David Pollack, Dmitriy Genzel, Donny Greenberg, Edward Z. Yang, Jason Lian, Jay Mahadeokar, Jeff Hwang, Ji Chen, Peter Goldsborough, Prabhat Roy, Sean Narenthiran, Shinji Watanabe, Soumith Chintala, Vincent Quenneville-Bélair, Yangyang Shi

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Tags: Computer science, Deep learning, Machine learning, nVidia, nVidia A100, Package, Python, PyTorch, Speech recognition

October 31, 2021 by hgpu

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

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLaMA-Inference-Bench

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MATAR

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Over-synchronization in GPU Programs

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

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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