high performance computing on graphics processing units: hgpu.org

Nicholas P. Bailey, Trond S. Ingebrigtsen, Jesper Schmidt Hansen, Arno A. Veldhorst, Lasse Bohling, Claire A. Lemarchand, Andreas E. Olsen, Andreas K. Bacher, Heine Larsen, Jeppe C. Dyre, Thomas B. Schroder

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Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 780 Ti, Package, Physics, Python

June 17, 2015 by hgpu

Exploring the Suitability of Remote GPGPU Virtualization for the OpenACC Programming Model Using rCUDA

Adrian Castello, Rafael Mayo, Enrique S. Quintana-Orti, Antonio J. Pena, Pavan Balaji

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Tesla C2050, Tesla K40, Virtualization

June 17, 2015 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

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high performance computing on graphics processing units: hgpu.org

Programming

DCT-JPEG Image Coding Based on GPU

Concurrent Task Execution on the Intel Xeon Phi

Comparative Study of the Parallelization of the Smith-Waterman Algorithm on OpenMP and Cuda C

GPU accelerated spectral finite elements on all-hex meshes

Generating Efficient Tensor Contractions for GPUs

Study of Sparse-Matrix Vector Multiplication (SpMV) on Different Architectures and Libraries

Autotuning Tensor Contraction Computations on GPUs

Bulk GCD Computation Using a GPU to Break Weak RSA Keys

Accelerated dimension-independent adaptive Metropolis

Visualization of OpenCL Application Execution on CPU-GPU Systems

RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles