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Performance and energy footprint assessment of FPGAs and GPUs on HPC systems using Astrophysics application

David Goz, Georgios Ieronymakis, Vassilis Papaefstathiou, Nikolaos Dimou, Sara Bertocco, Giuliano Taffoni, Francesco Simula, Antonio Ragagnin, Luca Tornatore, Igor Coretti

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Tags: ARM, Astrophysics, CUDA, FPGA, Heterogeneous systems, HPC, HSL, N-body simulation, nVidia, OpenCL, Performance, Physics, SoC, Tesla V100

March 15, 2020 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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