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Accelerating Haskell array codes with multicore GPUs

Manuel M.T. Chakravarty, Gabriele Keller, Sean Lee, Trevor L. McDonell, Vinod Grover

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Tags: Code generation, Computer science, CUBLAS, CUDA, Data parallelism, nVidia, Performance, Programming Languages, Tesla T10

August 22, 2011 by hgpu

A programming model for GPU-based parallel computing with scalability and abstraction

Balazs Domonkos, Gabor Jakab

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Tags: 3D Graphics and Realism, Computer science, CUDA, GPU cluster, MPI, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, OpenMP, Programming techniques

August 22, 2011 by hgpu

Sponge: portable stream programming on graphics engines

Amir H. Hormati, Mehrzad Samadi, Mark Woh, Trevor Mudge, Scott Mahlke

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Optimization, Performance, Programming Languages

August 21, 2011 by hgpu

Breaking the GPU programming barrier with the auto-parallelising SAC compiler

Jing Guo, Jeyarajan Thiyagalingam, Sven-Bodo Scholz

Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Performance, Programming Languages

August 21, 2011 by hgpu

GRace: a low-overhead mechanism for detecting data races in GPU programs

Mai Zheng, Vignesh T. Ravi, Feng Qin, Gagan Agrawal

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Tags: Algorithms, Computer science, CUDA, nVidia, Programming techniques, Tesla C1060

August 20, 2011 by hgpu

A framework for dynamically instrumenting GPU compute applications within GPU Ocelot

Naila Farooqui, Andrew Kerr, Gregory Diamos, S. Yalamanchili, K. Schwan

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Programming Languages, PTX

August 19, 2011 by hgpu

Extending abstract GPU APIs to shared memory

Ferosh Jacob

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Tags: Algorithms, Computer science, CUDA, nVidia, OpenCL, OpenMP, Presentation, Programming Languages, Programming techniques

August 19, 2011 by hgpu

A cluster for CS education in the manycore era

Joel C. Adams, Kathy Hoobeboom, Jonathan Walz

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, nVidia, OpenCL, OpenMP, OpenMPI, Performance

August 19, 2011 by hgpu

Caracal: dynamic translation of runtime environments for GPUs

Rodrigo Dominguez, Dana Schaa, David Kaeli

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Tags: ATI, ATI CAL, ATI IL, ATI Radeon HD 5870, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Performance, Programming Languages, PTX

August 19, 2011 by hgpu

Auto-tuning SkePU: a multi-backend skeleton programming framework for multi-GPU systems

Usman Dastgeer, Johan Enmyren, Christoph W. Kessler

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Tags: Computer science, CUDA, Data parallelism, nVidia, OpenCL, OpenMP, Package, Performance, Programming techniques, Tesla C1060

August 19, 2011 by hgpu

SkePU: a multi-backend skeleton programming library for multi-GPU systems

Johan Enmyren, Christoph W. Kessler

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Tags: Computer science, CUDA, Data parallelism, nVidia, OpenCL, OpenMP, Package, Performance, Programming techniques, Tesla C1060

August 18, 2011 by hgpu

Optimizing the exploitation of multicore processors and GPUs with OpenMP and OpenCL

Roger Ferrer, Judit Planas, Pieter Bellens, Alejandro Duran, Marc Gonzalez, Xavier Martorell, Rosa M. Badia, Eduard Ayguade, Jesus Labarta

Tags: Cell processor, Computer science, CUDA, GPU cluster, nVidia, OpenCL, OpenMP, Programming techniques

August 18, 2011 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Accelerating Haskell array codes with multicore GPUs

A programming model for GPU-based parallel computing with scalability and abstraction

Sponge: portable stream programming on graphics engines

Breaking the GPU programming barrier with the auto-parallelising SAC compiler

GRace: a low-overhead mechanism for detecting data races in GPU programs

A framework for dynamically instrumenting GPU compute applications within GPU Ocelot

Extending abstract GPU APIs to shared memory

A cluster for CS education in the manycore era

Caracal: dynamic translation of runtime environments for GPUs

Auto-tuning SkePU: a multi-backend skeleton programming framework for multi-GPU systems

SkePU: a multi-backend skeleton programming library for multi-GPU systems

Optimizing the exploitation of multicore processors and GPUs with OpenMP and OpenCL

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