high performance computing on graphics processing units: hgpu.org

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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

SemCache: Semantics-aware Caching for Efficient GPU Offloading

Nabeel AlSaber, Milind Kulkarni

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Tags: Computer science, CUDA, nVidia, Performance, Programming techniques, Tesla C2070

April 19, 2013 by hgpu

Geometric Algebra Computing Technology for Accelerated Processing Units

Patrick Charrier, Dietmar Hildenbrand

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Programming techniques

April 1, 2013 by hgpu

A Discussion of Selected Vienna-Libraries for Computational Science

Karl Rupp, Florian Rudolf, Josef Weinbub

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, OpenCL, Programming techniques, Review

April 1, 2013 by hgpu

Formal Analysis of GPU Programs with Atomics via Conflict-Directed Delay-Bounding

Wei-Fan Chiang, Ganesh Gopalakrishnan, Guodong Li, Zvonimir Rakamaric

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Tags: Computer science, CUDA, nVidia, Programming techniques

March 31, 2013 by hgpu

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Evaluation of Rust for GPGPU high performance computing

Evaluation of Rust for GPGPU high-performance computing

SCAMP: CPU/GPU Implementation of the SCAMP algorithm for computing the matrix profile

Optimization of massive data applications on heterogeneous architectures

A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code

FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Pulsar search acceleration using FPGAs and OpenCL templates

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

Fast Merge Tree Computation via SYCL

pocl: Portable Computing Language

Efficient OpenCL system integration of non-blocking FPGA accelerators

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

AutoDDL: Automatic Distributed Deep Learning with Asymptotically Optimal Communication

Python Suite for Advanced General Ensemble Simulations

PySAGES: flexible, advanced sampling methods accelerated with GPUs

GPU load-balancing library for regular and irregular computations

A Programming Model for GPU Load Balancing

See all packages

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high performance computing on graphics processing units: hgpu.org

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

SemCache: Semantics-aware Caching for Efficient GPU Offloading

Geometric Algebra Computing Technology for Accelerated Processing Units

A Discussion of Selected Vienna-Libraries for Computational Science

Formal Analysis of GPU Programs with Atomics via Conflict-Directed Delay-Bounding

Recent source codes

Evaluation of Rust for GPGPU high performance computing

SCAMP: CPU/GPU Implementation of the SCAMP algorithm for computing the matrix profile

A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code

FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

pocl: Portable Computing Language

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

Python Suite for Advanced General Ensemble Simulations

GPU load-balancing library for regular and irregular computations

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