high performance computing on graphics processing units: hgpu.org

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Parallel source code transformation techniques using design patterns

David del Rio Astorga

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Tags: Algorithms, Auto-Tuning, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Tesla K40, Thesis

December 2, 2018 by hgpu

Integration of CUDA Processing within the C++ library for parallelism and concurrency (HPX)

Patrick Diehl, Madhavan Seshadri, Thomas Heller, Hartmut Kaiser

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Tags: Computer science, CUDA, nVidia, Package, Programming Languages, Tesla K40, Tesla K80

November 3, 2018 by hgpu

OpenCL Performance Prediction using Architecture-Independent Features

Beau Johnston, Greg Falzon, Josh Milthorpe

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Tags: AMD FirePro S9150, AMD Radeon R9 290X, AMD Radeon R9 295X2, AMD Radeon RX 480, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 1080 Ti, OpenCL, Package, performance portability, Tesla K20, Tesla K40

November 3, 2018 by hgpu

On Reinforcement Learning for Full-length Game of StarCraft

Zhen-Jia Pang, Ruo-Ze Liu, Zhou-Yu Meng, Yi Zhang, Yang Yu, Tong Lu

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Tags: AI, Algorithms, Artificial intelligence, Computer science, Deep learning, Games, Machine learning, nVidia, Tesla K40

October 6, 2018 by hgpu

Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms

Nicholas J. Curtis, Kyle E. Niemeyer, Chih-Jen Sung

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Tags: Chemical Physics, Code generation, Computational Physics, Factorization, nVidia, OpenCL, Package, Physics, Tesla C2075, Tesla K40

September 9, 2018 by hgpu

Smoothed-Particle Hydrodynamics Models: Implementation Features on GPUs

Sergey Khrapov, Alexander Khoperskov

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Tags: Astrophysics, CUDA, hydrodynamics, nVidia, OpenMP, Tesla K20, Tesla K40, Tesla K80

July 28, 2018 by hgpu

Energy Consumption of Algorithms for Solving the Compressible Navier-Stokes Equations on CPU’s, GPU’s and KNL’s

Satya P. Jammy, Christian T. Jacobs, David J. Lusher, Neil D. Sandham

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Tags: CUDA, Finite difference, Fluid dynamics, Intel Xeon Phi, Navier-Stokes equations, NSEs, nVidia, Tesla K40

July 7, 2018 by hgpu

Directive-Based, High-Level Programming and Optimizations for High-Performance Computing with FPGAs

Jacob Lambert, Seyong Lee, Jungwon Kim, Jeffrey S. Vetter, Allen D. Malony

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Tags: Computer science, FPGA, nVidia, OpenACC, OpenCL, Tesla K40

July 1, 2018 by hgpu

Analysis-driven Engineering of Comparison-based Sorting Algorithms on GPUs

Ben Karsin, Volker Weichert, Henri Casanova, John Iacono, Nodari Sitchinava

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 770, nVidia Quadro M 4000, Performance, Sorting, Tesla K40

July 1, 2018 by hgpu

Strategies for the Heterogeneous Execution of Large-Scale Simulations on Hybrid Supercomputers

Xavier Alvarez, Andrey Gorobets, F. Xavier Trias

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Tags: cfd, Computational Physics, Fluid dynamics, Heterogeneous systems, HPC, Hybrid computing, MPI, nVidia, OpenCL, Sparse matrix, Tesla K40

June 24, 2018 by hgpu

DeepSmith: Compiler Fuzzing through Deep Learning

Chris Cummins, Pavlos Petoumenos, Alastair Murray, Hugh Leather

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Tags: Compilers, Computer science, Deep learning, nVidia, OpenCL, Package, Tesla K40

June 24, 2018 by hgpu

Dwarfs on Accelerators: Enhancing OpenCL Benchmarking for Heterogeneous Computing Architectures

Beau Johnston, Josh Milthorpe

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Tags: AMD FirePro S9150, AMD Radeon HD 7970, AMD Radeon R9 290X, AMD Radeon R9 Fury X, AMD Radeon RX 480, ATI, Benchmarking, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 1080, OpenCL, Tesla K20, Tesla K40

May 12, 2018 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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high performance computing on graphics processing units: hgpu.org

Parallel source code transformation techniques using design patterns

Integration of CUDA Processing within the C++ library for parallelism and concurrency (HPX)

OpenCL Performance Prediction using Architecture-Independent Features

On Reinforcement Learning for Full-length Game of StarCraft

Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms

Smoothed-Particle Hydrodynamics Models: Implementation Features on GPUs

Energy Consumption of Algorithms for Solving the Compressible Navier-Stokes Equations on CPU’s, GPU’s and KNL’s

Directive-Based, High-Level Programming and Optimizations for High-Performance Computing with FPGAs

Analysis-driven Engineering of Comparison-based Sorting Algorithms on GPUs

Strategies for the Heterogeneous Execution of Large-Scale Simulations on Hybrid Supercomputers

DeepSmith: Compiler Fuzzing through Deep Learning

Dwarfs on Accelerators: Enhancing OpenCL Benchmarking for Heterogeneous Computing Architectures

Recent source codes

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

IterApp: Iterative Application Skeleton

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

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