high performance computing on graphics processing units: hgpu.org

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Fast Simulation of Large-Scale Floods Based on GPU Parallel Computing

Qiang Liu, Yi Qin, Guodong Li

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Tags: Benchmarking, Earth and Space Sciences, Numerical simulation, nVidia, OpenACC, Tesla K20

May 5, 2018 by hgpu

Tiramisu: A Code Optimization Framework for High Performance Systems

Riyadh Baghdadi, Jessica Ray, Malek Ben Romdhane, Emanuele Del Sozzo, Patricia Suriana, Shoaib Kamil, Saman Amarasinghe

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Tags: Algorithms, Code generation, Computer science, CUDA, Distributed computing, FPGA, Heterogeneous systems, Linear Algebra, LLVM, MPI, nVidia, OpenMPI, Tesla K40

May 5, 2018 by hgpu

Multidimensional Parallelization for Streaming Text Processing Applications Based on Parabix Framework

Dan Lin

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Tags: Algorithms, Computer science, Data parallelism, LLVM, nVidia, nVidia GeForce GTX 950, Package, PTX, Thesis

April 28, 2018 by hgpu

A Comparative Study on Exact Triangle Counting Algorithms on the GPU

Leyuan Wang, Yangzihao Wang, Carl Yang, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Filtering, Graph theory, nVidia, Sparse matrix, Tesla K40

April 28, 2018 by hgpu

A Strategy for Automatic Performance Tuning of Stencil Computations on GPUs

Joseph D. Garvey, Tarek S. Abdelrahman

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Tags: AMD Radeon R9 390, ATI, Computer science, Machine learning, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance, Stencil computation

April 28, 2018 by hgpu

Accelerating Blockchain Search of Full Nodes Using GPUs

Shin Morishima, Hiroki Matsutani

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Tags: Computer science, CUDA, Finance, nVidia, nVidia GeForce GTX 980 Ti

April 28, 2018 by hgpu

Automatic generation of CUDA code performing tensor manipulations using C++ expression templates

Adam G.M. Lewis, Harald P. Pfeiffer

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Tags: Benchmarking, Code generation, Computer science, CUDA, General Relativity and Quantum Cosmology, nVidia, Tesla K80, Tesla M2090, Tesla P100

April 28, 2018 by hgpu

BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism

Nicolas Weber, Florian Schmidt, Mathias Niepert, Felipe Huici

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Tags: AI, Artificial intelligence, cache, CNN, Computer science, cpu, CUDA, Deep learning, GPU, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 1080 Ti

April 25, 2018 by hgpu

A Survey of Techniques for Dynamic Branch Prediction

Sparsh Mittal

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Tags: branch predictor, Paper, speculative execution, survey

April 25, 2018 by sparsh0mittal

CANNA: Neural Network Acceleration using Configurable Approximation on GPGPU

Mohsen Imani, Max Masich, Daniel Peroni, Pushen Wang, Tajana Rosing

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Tags: AMD Radeon HD 7970, ATI, Computer science, Deep learning, Neural networks, OpenCL

April 22, 2018 by hgpu

Fast inference of deep neural networks in FPGAs for particle physics

Javier Duarte, Song Han, Philip Harris, Sergo Jindariani, Edward Kreinar, Benjamin Kreis, Jennifer Ngadiuba, Maurizio Pierini, Nhan Tran, Zhenbin Wu

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Tags: Data acquisition, Deep learning, FPGA, HLS, Instrumentation and Detectors, Machine learning, Package, Physics

April 22, 2018 by hgpu

CytonRL: an Efficient Reinforcement Learning Open-source Toolkit Implemented in C++

Xiaolin Wang

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, OpenCV, Package

April 22, 2018 by hgpu

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

Engineering Supercomputing Platforms for Biomolecular Applications

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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high performance computing on graphics processing units: hgpu.org

Applications

Fast Simulation of Large-Scale Floods Based on GPU Parallel Computing

Tiramisu: A Code Optimization Framework for High Performance Systems

Multidimensional Parallelization for Streaming Text Processing Applications Based on Parabix Framework

A Comparative Study on Exact Triangle Counting Algorithms on the GPU

A Strategy for Automatic Performance Tuning of Stencil Computations on GPUs

Accelerating Blockchain Search of Full Nodes Using GPUs

Automatic generation of CUDA code performing tensor manipulations using C++ expression templates

BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism

A Survey of Techniques for Dynamic Branch Prediction

CANNA: Neural Network Acceleration using Configurable Approximation on GPGPU

Fast inference of deep neural networks in FPGAs for particle physics

CytonRL: an Efficient Reinforcement Learning Open-source Toolkit Implemented in C++

Recent source codes

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

microSYCL: SYCL micro-benchmarks repository

XaaS containers

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

SYCL Container

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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