high performance computing on graphics processing units: hgpu.org

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GPU Accelerated Scalable Parallel Random Number Generators

Shuang Gao, Gregory D. Peterson

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Tags: Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 480, Pseudo-random number generators, Tesla S1060

February 19, 2011 by hgpu

High-order finite-element seismic wave propagation modeling with MPI on a large GPU cluster

Dimitri Komatitsch, Gordon Erlebacher, Dominik Goddeke, David Michea

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Tags: Computational Physics, CUDA, Finite element method, Geoscience, GPU cluster, MPI, Numerical simulation, nVidia, Physics, Seismic modeling, Spectral elements, Tesla S1060, Tesla S1070

October 29, 2010 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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