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StencilFlow: Mapping Large Stencil Programs to Distributed Spatial Computing Systems

Johannes de Fine Licht, Andreas Kuster, Tiziano De Matteis, Tal Ben-Nun, Dominic Hofer, Torsten Hoefler

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Tags: Code generation, Computer science, CUDA, Distributed computing, FPGA, Heterogeneous systems, nVidia, OpenCL, Package, Tesla P100, Tesla V100

January 24, 2021 by hgpu

Exploiting BSP Abstractions for Compiler Based Optimizations of GPU Applications on multi-GPU Systems

Alexander Matz

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Tags: Benchmarking, Code generation, Compilers, Computer science, CUDA, nVidia, Package, Thesis

December 27, 2020 by hgpu

ANGHABENCH: a Suite with One Million Compilable C Benchmarks for Code-Size Reduction

Anderson Faustino da Silva, Bruno Conde Kind, Jose Wesley de Souza Magalhaes, Jeronimo Nunes Rocha, Breno Campos Ferreira Guimaraes, Fernando Magno Quintao Pereira

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Tags: Algorithms, Benchmarking, Code generation, Compiler, Computer science, LLVM, Package

December 20, 2020 by hgpu

Highly Efficient Lattice-Boltzmann Multiphase Simulations of Immiscible Fluids at High-Density Ratios on CPUs and GPUs through Code Generation

Markus Holzer, Martin Bauer, Harald Kostler, Ulrich Rüde

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Tags: Algorithms, cfd, Code generation, CUDA, Fluid dynamics, Lattice Boltzmann model, MPI, nVidia, OpenCL, Package, Physics, Programming techniques, Tesla P100, Tesla V100

December 20, 2020 by hgpu

Efficient code generation for hardware accelerators by refining partially specified implementation

Ulysse Beaugnon

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Tags: Algorithms, Code generation, Computer science, CUDA, Linear Algebra, nVidia, Optimization, Package, Thesis

December 13, 2020 by hgpu

Extending High-Level Synthesis for Task-Parallel Programs

Yuze Chi, Licheng Guo, Young-kyu Choi, Jie Wang, Jason Cong

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Tags: Code generation, Computer science, FPGA, HLS, OpenCL, Package

September 27, 2020 by hgpu

OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids

David J. Lusher, Satya P. Jammy, Neil D. Sandham

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Tags: cfd, Code generation, CUDA, Fluid dynamics, GPU cluster, Heterogeneous systems, Numerical simulation, nVidia, OpenCL, OpenMP, OpenMPI, Package, Python, Tesla P100

August 2, 2020 by hgpu

Compyle: a Python package for parallel computing

Aditya Bhosale, Prabhu Ramachandran

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Tags: Code generation, Computer science, CUDA, HPC, nVidia, OpenCL, Package, Python, Tesla P100

July 19, 2020 by hgpu

Investigating Input Representations and Representation Models of Source Code for Machine Learning

Alexander Brauckmann

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Tags: AMD Radeon HD 7970, ATI, Code generation, Computer science, LLVM, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 970, OpenCL, Thesis

July 12, 2020 by hgpu

Automated Partitioning of Data-Parallel Kernels using Polyhedral Compilation

Alexander Matz, Johannes Doerfert, Holger Fröning

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Tags: Code generation, Computer science, CUDA, LLVM, nVidia, Package, Tesla K80

July 12, 2020 by hgpu

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

Jiajian Xiao, Philipp Andelfinger, Wentong Cai, Paul Richmond, Alois Knoll, David Eckhoff

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Tags: Code generation, Computer science, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 2080 Ti, OpenCL, Package

June 7, 2020 by hgpu

From Constraint Programming to Heterogeneous Parallelism

Philip Ginsbach

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Tags: AMD Radeon R7, ATI, Code generation, Computer science, DSL, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan X, OpenCL, OpenMP, Thesis

May 10, 2020 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

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high performance computing on graphics processing units: hgpu.org

StencilFlow: Mapping Large Stencil Programs to Distributed Spatial Computing Systems

Exploiting BSP Abstractions for Compiler Based Optimizations of GPU Applications on multi-GPU Systems

ANGHABENCH: a Suite with One Million Compilable C Benchmarks for Code-Size Reduction

Highly Efficient Lattice-Boltzmann Multiphase Simulations of Immiscible Fluids at High-Density Ratios on CPUs and GPUs through Code Generation

Efficient code generation for hardware accelerators by refining partially specified implementation

Extending High-Level Synthesis for Task-Parallel Programs

OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids

Compyle: a Python package for parallel computing

Investigating Input Representations and Representation Models of Source Code for Machine Learning

Automated Partitioning of Data-Parallel Kernels using Polyhedral Compilation

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

From Constraint Programming to Heterogeneous Parallelism

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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