high performance computing on graphics processing units: hgpu.org

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Accelerating Drug Discovery in AutoDock-GPU with Tensor Cores

Gabin Schieffer, Ivy Peng

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Tags: Chemistry, Computer science, CUDA, Macromolecule, molecular docking, nVidia, nVidia A100, nVidia V100, Physics, Tesla T4

October 20, 2024 by hgpu

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

Anwar Hossain Zahid, Ignacio Laguna, Wei Le

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Tags: AMD Radeon Instinct MI250, ATI, Computer science, CUDA, HIP, Numerical Analysis, nVidia, nVidia V100, Programming Languages

October 20, 2024 by hgpu

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

Reza Abbasi, Sernam Lim

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Tags: AI, Artificial intelligence, Computer science, CUDA, LLM, Machine learning, Memory, nVidia, nVidia GeForce RTX 3090, nVidia Quadro RTX 8000, Package

October 20, 2024 by hgpu

Optimized Code Generation for Parallel and Polyhedral Loop Nests using MLIR

Arun Thangamani

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Tags: AMD Radeon Instinct Mi50, ATI, Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia A100, OpenCL, Thesis

October 13, 2024 by hgpu

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

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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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

Benchmarking Thread Block Cluster

Tim Lühnen, Tobias Marschner, Sohan Lal

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia H100, PTX

October 6, 2024 by hgpu

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

E.M. Garzón, J.A. Martínez, J.J. Moreno, M.L. Puertas

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Tags: Algorithms, Computer science, CUDA, Graph theory, HPC, nVidia, OpenMP, Package, Tesla V100

September 29, 2024 by hgpu

Automatic Generation of OpenCL Code through Polyhedral Compilation with LLM

Marek Palkowski, Mateusz Gruzewski

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Tags: AMD Radeon RX 6800, ATI, Code generation, Computer science, CUDA, LLM, nVidia, nVidia A100, OpenCL, OpenMP

September 29, 2024 by hgpu

EnergyUCB-Bandit

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

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

UVaFTLE: Lagrangian finite time Lyapunov exponent extraction for fluid dynamic applications

Challenging Portability Paradigms: FPGA Acceleration Using SYCL and OpenCL

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high performance computing on graphics processing units: hgpu.org

Accelerating Drug Discovery in AutoDock-GPU with Tensor Cores

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

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

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

Benchmarking Thread Block Cluster

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

Automatic Generation of OpenCL Code through Polyhedral Compilation with LLM

Recent source codes

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

MFC: Exascale simulation of multiphase/physics fluid dynamics

UVaFTLE: Lagrangian finite time Lyapunov exponent extraction for fluid dynamic applications

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