high performance computing on graphics processing units: hgpu.org

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Random Forests of Very Fast Decision Trees on GPU for Mining Evolving Big Data Streams

Diego Marron, Albert Bifet, Gianmarco De Francisci Morales

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Tags: Algorithms, Computer science, CUDA, Machine learning, nVidia, Tesla C2050

July 6, 2014 by hgpu

High-level Parallel Programming Support for Heterogeneous Systems

Bo Wu

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Tags: Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, OpenCL, Tesla C2050, Thesis

July 6, 2014 by hgpu

Exploiting parallel features of modern computer architectures in bioinformatics: applications to genetics, structure comparison and large graph analysis

Guillaume Chapuis

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Genetics, Graph theory, nVidia, Path problems, Tesla C2050, Thesis

July 3, 2014 by hgpu

Reducing the Code Degree Of Parallelism to Increase GPUs Reliability

P. Rech, L. Carro

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Tags: Computer science, CUDA, Fault simulation, nVidia, nVidia GeForce GTX 480, Tesla C2050

July 3, 2014 by hgpu

Using JavaScript and WebCL for Numerical Computations: A Comparative Study of Native and Web Technologies

Faiz Khan, Vincent Foley-Bourgon, Sujay Kathrotia, Erick Lavoie, Laurie Hendren

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Tags: ATI, ATI Radeon HD 7970, Benchmarking, Computer science, Java, nVidia, OpenCL, Package, Tesla C2050

June 23, 2014 by hgpu

The Power-Performance Tradeoffs of the Intel Xeon Phi on HPC Applications

Bo Li, Hung-Ching Chang, Shuaiwen Leon Song, Chun-Yi Su, Timmy Meyer, John Mooring, Kirk Cameron

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, nVidia, Performance, Tesla C2050

June 22, 2014 by hgpu

Medusa: A Parallel Graph Processing System on Graphics Processors

Jianlong Zhong, Bingsheng He

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Tags: Computer science, CUDA, Graph theory, nVidia, Package, Tesla C2050

June 19, 2014 by hgpu

Grover: Looking for Performance Improvement by Disabling Local Memory Usage in OpenCL Kernels

Jianbin Fang, Henk Sips, Pekka Jaaskelainen, Ana Lucia Varbanescu

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Tags: ATI, ATI Radeon HD 7970, Intel Xeon Phi, Local memory, nVidia, OpenCL, Reverse Engineering, Tesla C2050, Tesla K20

June 16, 2014 by jfang

Secure Distributed Computing on a Manycore Cloud

Flavio Lombardi

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Tags: Cloud, Computer science, CUDA, Data acquisition, Distributed computing, Heterogeneous systems, nVidia, nVidia GeForce GT 640, Security, Tesla C2050, Thesis

June 13, 2014 by hgpu

Optimization Techniques on GPU: A Survey

Rashmi Sharan Sinha, Satvir Singh

Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 285, Optimization, Overview, Particle swarm optimization, Tesla C1060, Tesla C2050

June 12, 2014 by hgpu

Software-Based Hardening Strategies for Neutron Sensitive FFT Algorithms on GPUs

L. L. Pilla, P. Rech, F. Silvestri, C. Frost, P. O. A. Navaux, M. Sonza Reorda, L. Carro

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Tags: Computer science, CUDA, Fault tolerance, FFT, nVidia, Tesla C2050

June 6, 2014 by hgpu

Utilizing Graphics Processing Units for Rapid Facial Recognition Using Video Input

Charles J. Gala

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Pattern recognition, Tesla C2050, Thesis

June 3, 2014 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Random Forests of Very Fast Decision Trees on GPU for Mining Evolving Big Data Streams

High-level Parallel Programming Support for Heterogeneous Systems

Exploiting parallel features of modern computer architectures in bioinformatics: applications to genetics, structure comparison and large graph analysis

Reducing the Code Degree Of Parallelism to Increase GPUs Reliability

Using JavaScript and WebCL for Numerical Computations: A Comparative Study of Native and Web Technologies

The Power-Performance Tradeoffs of the Intel Xeon Phi on HPC Applications

Medusa: A Parallel Graph Processing System on Graphics Processors

Grover: Looking for Performance Improvement by Disabling Local Memory Usage in OpenCL Kernels

Optimization Techniques on GPU: A Survey

Software-Based Hardening Strategies for Neutron Sensitive FFT Algorithms on GPUs

Utilizing Graphics Processing Units for Rapid Facial Recognition Using Video Input

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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