high performance computing on graphics processing units: hgpu.org

Martin Bauer, Sebastian Eibl, Christian Godenschwager, Nils Kohl, Michael Kuron, Christoph Rettinger, Florian Schornbaum, Christoph Schwarzmeier, Dominik Thönnes, Harald Köstler, Ulrich Rüde

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Tags: Code generation, CUDA, Heterogeneous systems, Lattice Boltzmann model, MPI, nVidia, Package, Particle simulation, performance portability, Physics, Tesla P100

October 6, 2019 by hgpu

ALPyNA: Acceleration of Loops in Python for Novel Architectures

Dejice Jacob, Jeremy Singer

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 1060, Python

September 22, 2019 by hgpu

Code optimization based on source to source transformations using profile guided metrics

Youenn Lebras

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Tags: Code generation, Computer science, Performance, Thesis

September 15, 2019 by hgpu

Compilers for Portable Programming of Heterogeneous Parallel & Approximate Computing Systems

Prakalp Srivastava

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Tags: Code generation, Computer science, Design space exploration, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL, performance portability

September 8, 2019 by hgpu

Position-Dependent Arrays and Their Application for High Performance Code Generation

Federico Pizzuti, Michel Steuwer, Christophe Dubach

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Tags: Code generation, Computer science, nVidia, nVidia GeForce GTX Titan X, OpenCL

August 25, 2019 by hgpu

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

EnergyUCB-Bandit

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

See all packages

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high performance computing on graphics processing units: hgpu.org

AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers

Accelerating Winograd Convolutions using Symbolic Computation and Meta-programming

md_poly: A Performance-Portable Polyhedral Compiler Based on Multi-Dimensional Homomorphisms

A Unified Iteration Space Transformation Framework for Sparse and Dense Tensor Algebra

Deep Learning Based FPGA-CPU Acceleration

Code Optimization on GPUs

waLBerla: A block-structured high-performance framework for multiphysics simulations

ALPyNA: Acceleration of Loops in Python for Novel Architectures

Code optimization based on source to source transformations using profile guided metrics

Compilers for Portable Programming of Heterogeneous Parallel & Approximate Computing Systems

Position-Dependent Arrays and Their Application for High Performance Code Generation

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

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

EnergyUCB-Bandit

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