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Optimizing OpenCL Kernels for Iterative Statistical Applications on GPUs

Thilina Gunarathne, Bimalee Salpitikorala, Arun Chauhan, Geoffrey Fox

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Tags: Algorithms, Code generation, Computer science, nVidia, OpenCL, Optimization, Statistics, Tesla C1060

September 25, 2011 by hgpu

Numerical Accuracy Differences in CPU and GPGPU Codes

Devon Yablonski

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Tags: Computer science, CUDA, Floating point error, nVidia, Tesla C1060, Thesis

September 25, 2011 by hgpu

The Test and Evaluation Uses of Heterogeneous Computing: GPGPUs and Other Approaches

Dan M. Davis, Gene Wagenbreth, Robert F. Lucas, Paul C. Gregory

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Tags: Computer science, Energy-efficient computing, Heterogeneous systems, nVidia, Overview, Tesla C1060

September 25, 2011 by hgpu

Algorithm Acceleration from GPGPUs for the ATLAS Upgrade

P.J. Clark, C. Jones, D. Emeilyanov, M. Rovatsou, A. Washbrook

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Tags: Algorithms, CUDA, High Energy Physics - Experiment, nVidia, Physics, Tesla C1060, Tesla C2050

September 25, 2011 by hgpu

OpenCL: a viable solution for high-performance medical image reconstruction?

Christian Siegl, H. G. Hofmann, B. Keck, M. Prummer, J. Hornegger

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Tags: ATI, ATI Radeon HD 5870, Image processing, Image reconstruction, nVidia, OpenCL, Optimization, Tesla C1060

September 24, 2011 by hgpu

Compact data structure and scalable algorithms for the sparse grid technique

Alin Murarasu, Josef Weidendorfer, Gerrit Buse, Daniel Butnaru, Dirk Pfluger

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Tags: Algorithms, Compression, Computer science, CUDA, Numerical Analysis, nVidia, Optimization, Programming techniques, Tesla C1060

September 23, 2011 by hgpu

On-the-fly elimination of dynamic irregularities for GPU computing

Eddy Z. Zhang, Yunlian Jiang, Ziyu Guo, Kai Tian, Xipeng Shen

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Optimization, Performance, Programming Languages, Tesla C1060

September 22, 2011 by hgpu

Acceleration of the speed of tissue characterization algorithm for coronary plaque by employing GPGPU technique

Takanori Koga, Shota Furukawa, Noriaki Suetake, Eiji Uchino

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Tags: Algorithms, CUDA, Medicine, Nearest neighbour, nVidia, Surgical simulation, Tesla C1060

September 22, 2011 by hgpu

Mint: realizing CUDA performance in 3D stencil methods with annotated C

Didem Unat, Xing Cai, Scott B. Baden

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Source codes

Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, OpenMP, Optimization, Package, Performance, Programming Languages, Tesla C1060

September 21, 2011 by hgpu

CuMAPz: a tool to analyze memory access patterns in CUDA

Yooseong Kim, Aviral Shrivastava

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Tags: Analytical model, Benchmarking, Computer science, CUDA, Memory, nVidia, Performance, Tesla C1060

September 20, 2011 by hgpu

The TheLMA project: Multi-GPU implementation of the lattice Boltzmann method

Christian Obrecht, Frederic Kuznik, Bernard Tourancheau, Jean-Jacques Roux

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Tags: CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, nVidia, Presentation, Tesla C1060

September 19, 2011 by hgpu

A GPU-tailored approach for training kernelized SVMs

Andrew Cotter, Nathan Srebro, Joseph Keshet

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Tags: Algorithms, Clustering, Computer science, nVidia, Optimization, Package, Performance, Programming techniques, Tesla C1060

September 19, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Optimizing OpenCL Kernels for Iterative Statistical Applications on GPUs

Numerical Accuracy Differences in CPU and GPGPU Codes

The Test and Evaluation Uses of Heterogeneous Computing: GPGPUs and Other Approaches

Algorithm Acceleration from GPGPUs for the ATLAS Upgrade

OpenCL: a viable solution for high-performance medical image reconstruction?

Compact data structure and scalable algorithms for the sparse grid technique

On-the-fly elimination of dynamic irregularities for GPU computing

Acceleration of the speed of tissue characterization algorithm for coronary plaque by employing GPGPU technique

Mint: realizing CUDA performance in 3D stencil methods with annotated C

CuMAPz: a tool to analyze memory access patterns in CUDA

The TheLMA project: Multi-GPU implementation of the lattice Boltzmann method

A GPU-tailored approach for training kernelized SVMs

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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