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A Framework for Productive, Efficient and Portable Parallel Computing

Ekaterina I. Gonina

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Tags: Algorithms, Code generation, Computer science, CUDA, MapReduce, nVidia, nVidia GeForce GTX 480, Package, Python, Thesis

January 12, 2014 by hgpu

DEF-G: Declarative Framework for GPU Environment

Robert Senser, Tom Altman

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Tags: Code generation, Computer science, Filtering, nVidia, nVidia GeForce GT 430, OpenCL, Tesla T20

January 5, 2014 by hgpu

Multilayered Abstractions for Partial Differential Equations

Graham Robert Markall

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Code generation, CUDA, Differential equations, FEM, Finite element method, Mathematics, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Partial differential equations, PDEs, Software Engineering, Thesis

December 11, 2013 by hgpu

A Methodology for Translating C-Programs to OpenCL

Krishnahari Thouti, S. R. Sathe

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Tags: Code generation, Compilers, Computer science, nVidia, nVidia Quadro FX 3800, OpenCL, Programming Languages

November 16, 2013 by hgpu

SAGE: Self-Tuning Approximation for Graphics Engines

Mehrzad Samadi, Janghaeng Lee, D. Anoushe Jamshidi, Amir Hormati, Scott Mahlke

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Tags: Algorithms, Code generation, Compilers, CUDA, Image processing, Machine learning, nVidia, nVidia GeForce GTX 560, Performance

November 14, 2013 by hgpu

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Michal Januszewski, Marcin Kostur

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Tags: Code generation, Computational Physics, CUDA, Fluid dynamics, Fluid simulation, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 285, OpenCL, Package, Physics, Python, Tesla C1060, Tesla C2050, Tesla K10, Tesla K20

November 12, 2013 by hgpu

Automatic Synthesis of Heterogeneous CPU-GPU Embedded Applications from a UML Profile

Federico Ciccozzi

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia

November 8, 2013 by hgpu

Towards Code Generation from Design Models for Embedded Systems on Heterogeneous CPU-GPU Platforms

Federico Ciccozzi

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia

October 18, 2013 by hgpu

Domain-Specific Languages for Heterogeneous Parallel Computing

HyoukJoong Lee, Kevin J. Brown, Arvind K. Sujeeth, Hassan Chafi, Tiark Rompf, Martin Odersky, Kunle Olukotun

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, Tesla C2050

October 15, 2013 by hgpu

Speculative Execution of Parallel Programs with Precise Exception Semantics on GPUs

Akihiro Hayashi, Max Grossman, Jisheng Zhao, Jun Shirako, Vivek Sarkar

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Tags: Code generation, Computer science, Java, nVidia, OpenCL, Tesla M2050

October 5, 2013 by hgpu

Parametric GPU Code Generation for Affine Loop Programs

Athanasios Konstantinidis, Paul H. J. Kelly, J. Ramanujam, P. Sadayappan

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GT 540 M, nVidia GeForce GTX 580, OpenCL, Package, Tesla K20, Tesla M2070

October 5, 2013 by hgpu

Compiler Optimizations for SIMD/GPU/Multicore Architectures

Jun Liu

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Tags: Code generation, Compilers, Computer science, CUDA, Data parallelism, nVidia, Tesla C2050, Thesis

October 3, 2013 by hgpu

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

A Framework for Productive, Efficient and Portable Parallel Computing

DEF-G: Declarative Framework for GPU Environment

Multilayered Abstractions for Partial Differential Equations

A Methodology for Translating C-Programs to OpenCL

SAGE: Self-Tuning Approximation for Graphics Engines

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Automatic Synthesis of Heterogeneous CPU-GPU Embedded Applications from a UML Profile

Towards Code Generation from Design Models for Embedded Systems on Heterogeneous CPU-GPU Platforms

Domain-Specific Languages for Heterogeneous Parallel Computing

Speculative Execution of Parallel Programs with Precise Exception Semantics on GPUs

Parametric GPU Code Generation for Affine Loop Programs

Compiler Optimizations for SIMD/GPU/Multicore Architectures

Recent source codes

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

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