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NaturalCC: A Toolkit to Naturalize the Source Code Corpus

Yao Wan, Yang He, Jian-Guo Zhang, Yulei Sui, Hai Jin, Guandong Xu, Caiming Xiong, Philip S. Yu

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Tags: Computer science, CUDA, Deep learning, NLP, nVidia, Package, Programming Languages, Python, Video

December 13, 2020 by hgpu

Transparent Compiler and Runtime Specializations for Accelerating Managed Languages on FPGAs

Michail Papadimitriou, Juan Fumero, Athanasios Stratikopoulos, Foivos S. Zakkak, Christos Kotselidis

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Tags: Computer science, FPGA, HLS, Java, OpenCL, Optimization, Package, Programming Languages

November 8, 2020 by hgpu

AnyHLS: High-Level Synthesis with Partial Evaluation

M. Akif Özkan, Arsène Pérard-Gayot, Richard Membarth, Philipp Slusallek, Roland Leissa, Sebastian Hack, Jürgen Teich, Frank Hannig

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Tags: Computer science, FPGA, HLS, Image processing, OpenCL, Package, Programming Languages

August 9, 2020 by hgpu

Automatic Kernel Generation for Volta Tensor Cores

Somashekaracharya G. Bhaskaracharya, Julien Demouth, Vinod Grover

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Tags: Compilers, Computer science, CUBLAS, CUDA, Deep learning, Matrix multiplication, nVidia, nVidia Quadro GV100, Performance, Programming Languages, PTX

June 28, 2020 by hgpu

Parallel Programming Models for Heterogeneous Many-Cores: A Survey

Jianbin Fang, Chun Huang, Tao Tang, Zheng Wang

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Optimization, Programming Languages, Review

May 17, 2020 by hgpu

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

Chris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Hugh Leather

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Tags: Computer science, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 970, OpenCL, Package, Performance, Programming Languages

March 29, 2020 by hgpu

Fireiron: A Scheduling Language for High-Performance Linear Algebra on GPUs

Bastian Hagedorn, Archibald Samuel Elliott, Henrik Barthels, Rastislav Bodik, Vinod Grover

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce RTX 2080 Ti, nVidia Quadro GV100, Programming Languages

March 22, 2020 by hgpu

Memory-Efficient Object-Oriented Programming on GPUs

Matthias Springer

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 940 M, nVidia GeForce GTX 980, nVidia GeForce GTX Titan XP, Package, Programming Languages, Thesis

August 25, 2019 by hgpu

On the Representation of Partially Specified Implementations and its Application to the Optimization of Linear Algebra Kernels on GPU

Ulysse Beaugnon, Basile Clément, Nicolas Tollenaere, Albert Cohen

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Tags: Analytical model, Computer science, CUDA, Linear Algebra, nVidia, nVidia Quadro K4000, Programming Languages

April 14, 2019 by hgpu

AutoPhase: Compiler Phase-Ordering for High Level Synthesis with Deep Reinforcement Learning

Ameer Haj-Ali, Qijing Huang, William Moses, John Xiang, Ion Stoica, Krste Asanovic, John Wawrzynek

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Tags: Algorithms, Code generation, Compilers, Computer science, Deep learning, HLS, LLVM, Programming Languages

January 20, 2019 by hgpu

Automatic acceleration of Numpy applications on GPUs and multicore CPUs

Mahesh Ravishankar, Vinod Grover

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Tags: Computer science, nVidia, Programming Languages

January 20, 2019 by hgpu

Integration of CUDA Processing within the C++ library for parallelism and concurrency (HPX)

Patrick Diehl, Madhavan Seshadri, Thomas Heller, Hartmut Kaiser

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Tags: Computer science, CUDA, nVidia, Package, Programming Languages, Tesla K40, Tesla K80

November 3, 2018 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

NaturalCC: A Toolkit to Naturalize the Source Code Corpus

Transparent Compiler and Runtime Specializations for Accelerating Managed Languages on FPGAs

AnyHLS: High-Level Synthesis with Partial Evaluation

Automatic Kernel Generation for Volta Tensor Cores

Parallel Programming Models for Heterogeneous Many-Cores: A Survey

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

Fireiron: A Scheduling Language for High-Performance Linear Algebra on GPUs

Memory-Efficient Object-Oriented Programming on GPUs

On the Representation of Partially Specified Implementations and its Application to the Optimization of Linear Algebra Kernels on GPU

AutoPhase: Compiler Phase-Ordering for High Level Synthesis with Deep Reinforcement Learning

Automatic acceleration of Numpy applications on GPUs and multicore CPUs

Integration of CUDA Processing within the C++ library for parallelism and concurrency (HPX)

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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