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The Future of Accelerator Programming: Abstraction, Performance or Can We Have Both?

Kamil Rocki, Martin Burtscher, Reiji Suda

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Tags: ATI, ATI Radeon HD 7970, Computer science, Intel Phi, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance, Programming techniques

November 28, 2013 by hgpu

Specification and verification of GPGPU programs

Stefan Blom, Marieke Huisman and Matej Mihelcic

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Tags: Computer science, OpenCL, Programming techniques

November 18, 2013 by hgpu

Performance analysis of SSE instructions in multi-core CPUs and GPU computing on FDTD scheme for solid and fluid vibration problems

Jorge Frances Monllor, Sergio Bleda Perez, Andres Marquez Ruiz, Cristian Neipp Lopez, Sergi Gallego Rico, Beatriz Otero Calvino, Augusto Belendez Vazquez

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Tags: CUDA, FDTD, Finite-difference time-domain, Fluid dynamics, nVidia, nVidia GeForce GTX 470, Programming techniques

September 15, 2013 by hgpu

A Bi-objective Optimization Framework for Query Plans

P. Przymus, K. Kaczmarski, K. Stencel

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Tags: Heterogeneous systems, Performance, Programming techniques

September 7, 2013 by hgpu

Accurate Analytic Models to Estimate Execution Time on GPU Applications

Pedro Velho, Daniel A. G. de Oliveira, Edson L. Padoin, Philippe O. A. Navaux

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance, Programming techniques

August 21, 2013 by hgpu

Portable HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi

Jack Dongarra, Mark Gates, Azzam Haidar, Yulu Jia, Khairul Kabir, Piotr Luszczek, Stanimire Tomov

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Tags: Computer science, Heterogeneous systems, Intel Phi, Linear Algebra, Package, Programming techniques

July 30, 2013 by hgpu

Megakernels Considered Harmful: Wavefront Path Tracing on GPUs

Samuli Laine, Tero Karras, Timo Aila

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, Programming techniques, Raytracing, Tesla K20

June 19, 2013 by hgpu

Accelerated Dynamic Programming on GPU: A Study of Speed Up and Programming Approach

Mohsin Altaf Wani, S.M.K Quadri

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 570, Optimization, Programming techniques

June 8, 2013 by hgpu

Modernizing the core quantum chemistry algorithms

Andrey Asadchev

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Tags: Algorithms, Chemistry, Computational chemistry, CUDA, nVidia, Programming techniques, Tesla C2050, Thesis

June 8, 2013 by hgpu

Parallelization & checkpointing of GPU applications through program transformation

Lizandro Damian Solano-Quinde

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Tags: Computer science, nVidia, OpenCL, Programming techniques, Tesla C2070, Tesla T10, Thesis

June 6, 2013 by hgpu

Effects of Concurrency Techniques and Algorithm Performance: A Comparative Analysis of Single-Threaded, Multi-Threaded, and GPGPU Programming Techniques

Joshua Penton

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Tags: ATI, ATI Radeon HD 6750 M, Computer science, FFT, Java, OpenCL, Package, Performance, Programming techniques

May 28, 2013 by hgpu

Graphics processing unit (GPU) programming strategies and trends in GPU computing

Andre R. Brodtkorb, Trond R. Hagen, Martin L. Saetra

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Tags: Computer science, Heterogeneous systems, Metaheuristics, Optimization, Overview, Programming techniques

April 19, 2013 by hgpu

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

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

The Future of Accelerator Programming: Abstraction, Performance or Can We Have Both?

Specification and verification of GPGPU programs

Performance analysis of SSE instructions in multi-core CPUs and GPU computing on FDTD scheme for solid and fluid vibration problems

A Bi-objective Optimization Framework for Query Plans

Accurate Analytic Models to Estimate Execution Time on GPU Applications

Portable HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi

Megakernels Considered Harmful: Wavefront Path Tracing on GPUs

Accelerated Dynamic Programming on GPU: A Study of Speed Up and Programming Approach

Modernizing the core quantum chemistry algorithms

Parallelization & checkpointing of GPU applications through program transformation

Effects of Concurrency Techniques and Algorithm Performance: A Comparative Analysis of Single-Threaded, Multi-Threaded, and GPGPU Programming Techniques

Graphics processing unit (GPU) programming strategies and trends in GPU computing

Recent source codes

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

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

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