high performance computing on graphics processing units: hgpu.org

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Many-Core Compiler Fuzzing

Christopher Lidbury, Andrei Lascu, Nathan Chong, Alastair F. Donaldson

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Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Compilers, Computer science, FPGA, Intel HD 4600, Intel Xeon Phi, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX Titan, OpenCL, Tesla K40, Tesla M2050

July 10, 2015 by hgpu

Falcon: A Graph Manipulation Language for Heterogeneous Systems

Unnikrishnan C, Y N Srikant, Rupesh Nasre

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Tags: Compilers, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, OpenMP, Tesla C2050, Tesla C2075, Tesla K20

June 16, 2015 by hgpu

OMP2HMPP: Compiler Framework for Energy-Performance Trade-off Analysis of Automatically Generated Codes

Albert Saa-Garriga, David Castells-Rufas, Jordi Carrabina

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, Tesla M2050

May 5, 2015 by hgpu

Generating Performance Portable Code using Rewrite Rules: From High-level Functional Expressions to High-Performance OpenCL Code

Michel Steuwer, Christian Fensch, Sam Lindley, Christophe Dubach

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Tags: ATI, ATI Radeon HD 7970, Code generation, Compilers, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL

March 8, 2015 by hgpu

Compiler-Level Explicit Cache for a GPGPU Programming Framework

Tomoharu Kamiya, Takanori Maruyama, Kazuhiko Ohno, Masaki Matsumoto

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Tesla C2050, Tesla K20

December 12, 2014 by hgpu

A Validation Testsuite for OpenACC 1.0

Cheng Wang, Rengan Xu, Sunita Chandrasekaran, Barbara Chapman, Oscar Hernandez

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Tags: Compilers, Computer science, Fortran, nVidia, OpenACC, Tesla K20

September 9, 2014 by hgpu

A CUDA Back-End for the Equelle Compiler

Havard Heitlo Holm

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Source codes

Tags: Compilers, Computer science, CUDA, Differential equations, Finite volume method, Heterogeneous systems, nVidia, nVidia Quadro NVS 5200 M, Package, Partial differential equations, PDEs, Tesla K40, Thesis

September 8, 2014 by hgpu

Directive-Based Compilers for GPUs

Swapnil Ghike, Ruben Gran, Maria J. Garzaran, David Padua

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, OpenACC, Tesla X2090

September 2, 2014 by hgpu

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Moritz Schmid, Oliver Reiche, Christian Schmitt, Frank Hannig, Jurgen Teich

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Tags: ARM, Code generation, Compilers, Computational Complexity, Computer science, Differential equations, FPGA, Image processing, Partial differential equations, PDEs

August 23, 2014 by hgpu

Integrating Profiling into MDE Compilers

Vincent Aranega, A. Wendell O. Rodrigues, Anne Etien, Frederic Guyomarch, Jean-Luc Dekeyser

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Tags: Compilers, Computer science, nVidia, OpenCL, Tesla S1070, Tesla T10

August 3, 2014 by hgpu

Automatic Parallelization of Tiled Stencil Loop Nests on GPUs

Peng Di

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Performance, Tesla C1060, Tesla C2050, Thesis

July 30, 2014 by hgpu

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

Albert Saa-Garriga, David Castells-Rufas, Jordi Carrabina

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C2075, Tesla K20, Tesla M2050

July 28, 2014 by hgpu

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

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

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

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high performance computing on graphics processing units: hgpu.org

Many-Core Compiler Fuzzing

Falcon: A Graph Manipulation Language for Heterogeneous Systems

OMP2HMPP: Compiler Framework for Energy-Performance Trade-off Analysis of Automatically Generated Codes

Generating Performance Portable Code using Rewrite Rules: From High-level Functional Expressions to High-Performance OpenCL Code

Compiler-Level Explicit Cache for a GPGPU Programming Framework

A Validation Testsuite for OpenACC 1.0

A CUDA Back-End for the Equelle Compiler

Directive-Based Compilers for GPUs

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Integrating Profiling into MDE Compilers

Automatic Parallelization of Tiled Stencil Loop Nests on GPUs

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

Recent source codes

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

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

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