high performance computing on graphics processing units: hgpu.org

Ming Li, Ziqian Bi, Tianyang Wang, Yizhu Wen, Qian Niu, Junyu Liu, Benji Peng, Sen Zhang, Xuanhe Pan, Jiawei Xu, Jinlang Wang, Keyu Chen, Caitlyn Heqi Yin, Pohsun Feng, Ming Liu

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Tags: Book, Computer science, CUDA, Deep learning, FPGA, Machine learning, nVidia, OpenCL, OpenGL, TPU, Vulkan

October 13, 2024 by hgpu

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Dennis Liew, Tiago Cogumbreiro, Julien Lange

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Source codes

Tags: Artificial intelligence, Computer science, CUDA, nVidia, Package, Performance

October 13, 2024 by hgpu

A domain-specific language for geospatial computations on the GPU

Louise Tidestav

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Tags: Computer science, CUDA, DSL, nVidia, nVidia Quadro P 2000, Thesis

October 13, 2024 by hgpu

Efficient Arbitrary Precision Acceleration for Large Language Models on GPU Tensor Cores

Shaobo Ma, Chao Fang, Haikuo Shao, Zhongfeng Wang

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Tags: Computer science, CUDA, Data recovery, Extended precision, LLM, Matrix multiplication, nVidia, nVidia GeForce RTX 3090, Security

October 6, 2024 by hgpu

Event-Based OpenMP Tasks for Time-Sensitive GPU-Accelerated Systems

Cyril Cetre, Chenle Yu, Sara Royuela, Rémi Barrere, Eduardo Quiñones, Damien Gratadour

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, CUDA, HIP, HPC, nVidia, nVidia A100, Performance

October 6, 2024 by hgpu

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

Faial: finds bugs in CUDA kernels

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL

miniLB: Lattice Botlzmann miniapp w/SYCL

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

AFOCL

Bitstream Database-Driven FPGA Programming Flow Based on Standard OpenCL

2domination

HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

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high performance computing on graphics processing units: hgpu.org

General-Purpose Computing on Tensor Processors

Using modern C++ to improve CUDA programs

Testing GPU Numerics: Finding Numerical Differences Between NVIDIA and AMD GPUs

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

Accelerating Drug Discovery in AutoDock-GPU with Tensor Cores

Optimized Code Generation for Parallel and Polyhedral Loop Nests using MLIR

Deep Learning and Machine Learning with GPGPU and CUDA: Unlocking the Power of Parallel Computing

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

A domain-specific language for geospatial computations on the GPU

Efficient Arbitrary Precision Acceleration for Large Language Models on GPU Tensor Cores

Event-Based OpenMP Tasks for Time-Sensitive GPU-Accelerated Systems

Recent source codes

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

EnergyUCB-Bandit

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

Faial: finds bugs in CUDA kernels

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

miniLB: Lattice Botlzmann miniapp w/SYCL

AFOCL

2domination

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