high performance computing on graphics processing units: hgpu.org

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Energy-Efficient Collective Reduce and Allreduce Operations on Distributed GPUs

Lena Oden, Benjamin Klenk, Holger Froning

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Tags: Computer science, CUDA, Distributed computing, Energy-efficient computing, Heterogeneous systems, nVidia, Tesla K20

July 17, 2014 by hgpu

Infiniband-Verbs on GPU: A case study of controlling an Infiniband network device from the GPU

Lena Oden, Holger Froning, Franz-Joseph Pfreundt

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, Networks, nVidia, Tesla K20

July 14, 2014 by hgpu

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

Aditya Deshpande

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Tags: Algorithms, Compression, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 580, nVidia Quadro FX 3700, Package, Sorting, Sparse matrix, Tesla K20, Thesis

July 11, 2014 by hgpu

Programming-Model Centric Debugging for Multicore Embedded Systems

Kevin Pouget

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Tags: Computer science, CUDA, H.264/AVC, nVidia, OpenCL, Programming techniques, Tesla K20, Thesis, Video decoding

July 11, 2014 by hgpu

Massive Parallelism with GPUs for Centrality Ranking in Complex Networks

Frederico L. Cabral, Carla Osthoff, Rafael Nardes, Daniel Ramos

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Tags: Computer science, CUDA, GPU cluster, Graph theory, MPI, nVidia, Tesla K20

July 6, 2014 by hgpu

Writing self-adaptive codes for heterogeneous systems

Jorge F. Fabeiro, Diego Andrade, Basilio B. Fraguela, Ramon Doallo

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Package, Tesla K20

July 4, 2014 by hgpu

Historic Learning Approach for Auto-tuning OpenACC Accelerated Scientific Applications

Shahzeb Siddiqui, Saber Feki

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Tags: Computer science, CUDA, nVidia, OpenACC, Performance, Tesla K20

July 3, 2014 by hgpu

Toward Auto-tuned Krylov Basis Computations with minimized Communication on Clusters of Accelerators

Langshi Chen, Serge Petiton, Leroy Drummond, Maxime Hugues

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Tesla K20

July 3, 2014 by hgpu

Mixed-precision Orthogonalization Scheme and Adaptive Step Size for CA-GMRES on GPUs

Ichitaro Yamazaki, Stanimire Tomov, Tingxing Dong, Jack Dongarra

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Tags: Computer science, Linear Algebra, nVidia, Performance, Tesla K20, Tesla K40, Tesla M2090

July 1, 2014 by hgpu

Kd-tree Based N-Body Simulations with Volume-Mass Heuristic on the GPU

Klaus Kofler, Dominik Steinhauser, Biagio Cosenza, Ivan Grasso, Sabine Schindler, Thomas Fahringer

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Tags: Algorithms, Astrophysics, ATI, ATI Radeon HD 5870, ATI Radeon HD 7950, Computational Complexity, Computer science, KD-tree, N-body simulation, nVidia, nVidia GeForce GTX 480, OpenCL, Tesla K20

July 1, 2014 by hgpu

Preemptive Thread Block Scheduling with Online Structural Runtime Prediction for Concurrent GPGPU Kernels

Sreepathi Pai, R. Govindarajan, Matthew J. Thazhuthaveetil

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Tags: Computer science, CUDA, nVidia, Operating systems, Performance, Tesla K20

June 25, 2014 by hgpu

Feature Generation for Quantification of Visual Similarity

Tianning Steven Han

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Tags: Algorithms, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 480, Tesla K20, Thesis

June 23, 2014 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Energy-Efficient Collective Reduce and Allreduce Operations on Distributed GPUs

Infiniband-Verbs on GPU: A case study of controlling an Infiniband network device from the GPU

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

Programming-Model Centric Debugging for Multicore Embedded Systems

Massive Parallelism with GPUs for Centrality Ranking in Complex Networks

Writing self-adaptive codes for heterogeneous systems

Historic Learning Approach for Auto-tuning OpenACC Accelerated Scientific Applications

Toward Auto-tuned Krylov Basis Computations with minimized Communication on Clusters of Accelerators

Mixed-precision Orthogonalization Scheme and Adaptive Step Size for CA-GMRES on GPUs

Kd-tree Based N-Body Simulations with Volume-Mass Heuristic on the GPU

Preemptive Thread Block Scheduling with Online Structural Runtime Prediction for Concurrent GPGPU Kernels

Feature Generation for Quantification of Visual Similarity

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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