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Reducing data access latency in SDSM systems using runtime optimizations

Javier Bueno, Xavier Martorell, Juan Jose Costa, Toni Cortes, Eduard Ayguade, Guansong Zhang, Christopher Barton, Raul Silvera

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Tags: Computer science, Distributed data structures, OpenCL, OpenMP, Performance, Programming Languages

August 21, 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

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

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

ForOpenCL: Transformations Exploiting Array Syntax in Fortran for Accelerator Programming

Matthew J. Sottile, Craig E Rasmussen, Wayne N. Weseloh, Robert W. Robey, Daniel Quinlan, Jeffrey Overbey

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Tags: Computer science, Fortran, nVidia, OpenCL, Package, Programming Languages, Tesla C2050

July 14, 2011 by hgpu

Accelerating QDP++ using GPUs

Frank Winter

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Tags: Computational Physics, CUDA, High Energy Physics - Lattice, nVidia, nVidia GeForce GTX 480, Physics, Programming Languages, QCD

May 12, 2011 by hgpu

Data-aware scheduling of legacy kernels on heterogeneous platforms with distributed memory

Michela Becchi, Surendra Byna, Srihari Cadambi, Srimat Chakradhar

Tags: Computer science, CUDA, Distributed data structures, Heterogeneous systems, nVidia, Performance, Programming Languages, Sparse matrix, Tesla C870

May 10, 2011 by hgpu

Ocelot: a dynamic optimization framework for bulk-synchronous applications in heterogeneous systems

Gregory F. Diamos, Andrew R. Kerr, Sudhakar Yalamanchili, Nathan Clark

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Programming Languages, PTX

March 9, 2011 by hgpu

A Tuning Framework for Software-Managed Memory Hierarchies

Manman Ren, Ji Young Park, Mike Houston, Alex Aiken, William J. Dally

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Tags: Algorithms, Cell processor, Compilers, Computer science, Optimization, Performance, Playstation, Programming Languages

February 26, 2011 by hgpu

Many-core GPU computing with NVIDIA CUDA

Mark Harris

Tags: Computer science, CUDA, High-level Languages, nVidia, Programming Languages

February 24, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

Reducing data access latency in SDSM systems using runtime optimizations

Sponge: portable stream programming on graphics engines

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

A framework for dynamically instrumenting GPU compute applications within GPU Ocelot

Extending abstract GPU APIs to shared memory

Caracal: dynamic translation of runtime environments for GPUs

ForOpenCL: Transformations Exploiting Array Syntax in Fortran for Accelerator Programming

Accelerating QDP++ using GPUs

Data-aware scheduling of legacy kernels on heterogeneous platforms with distributed memory

Ocelot: a dynamic optimization framework for bulk-synchronous applications in heterogeneous systems

A Tuning Framework for Software-Managed Memory Hierarchies

Many-core GPU computing with NVIDIA CUDA

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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