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Efficient Implementation of MrBayes on multi-GPU

Jie Bao, Hongju Xia, Jianfu Zhou, Xiaoguang Liu, Gang Wang

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Tags: Bayesian, Biology, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 480, Package, Task scheduling

January 28, 2013 by hgpu

A dataflow-like programming model for future hybrid clusters

Jens Breitbart

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Tags: Cluster computing, Computer science, CUDA, Distributed data structures, Hybrid computing, nVidia, nVidia GeForce GTX 480, Tesla C2050

January 28, 2013 by hgpu

Exploring Different Automata Representations for Efficient Regular Expression Matching on GPUs

Xiaodong Yu, Michela Becchi

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Tags: Cellular automata, Computer science, CUDA, nVidia, Performance, Security

January 28, 2013 by hgpu

Warped Register File: A Power Efficient Register File for GPGPUs

Mohammad Abdel-Majeed, Murali Annavaram

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, Performance

January 28, 2013 by hgpu

Reaction-diffusion model Monte Carlo simulations on the GPU

Raoul D. Schram

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Tags: Computational Physics, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, OpenCL, Physics, Statistical Mechanics

January 28, 2013 by hgpu

GPUfs: Integrating a File System with GPUs

Mark Silberstein, Bryan Ford, Idit Keidar, Emmett Witchel

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Tags: Computer science, CUDA, nVidia, Operating systems, Tesla C2075

January 26, 2013 by hgpu

Advanced Trends of Heterogeneous Computing with CPU-GPU Integration: Comparative Study

Ishan Rajani, G Nanda Gopal

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Tags: AMD FireStream 9270, ATI, Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, OpenCL, Tesla C2050, Warp level parallelism

January 26, 2013 by hgpu

Selection algorithm of graphic accelerators in heterogeneous cluster for optimization computing

A. M. Lavreniuk, M. S. Lavreniuk

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Tags: Algorithms, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, OpenCL, Tesla M2050

January 26, 2013 by hgpu

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

Malik Muhammad Zaki Murtaza Khan

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Tags: Code generation, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2050, Thesis

January 26, 2013 by hgpu

Automatic Parallelization for GPUs

Thomas B. Jablin

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Programming techniques, Thesis

January 26, 2013 by hgpu

Orthogonalization on a General Purpose Graphics Processing Unit with Double Double and Quad Double Arithmetic

Jan Verschelde, Genady Yoffe

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Tags: Algorithms, CUDA, Extended precision, Mathematics, nVidia, Tesla C2050

January 25, 2013 by hgpu

Regularization and nonlinearities for neural language models: when are they needed?

Marius Pachitariu, Maneesh Sahani

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Tags: CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 680, Statistics

January 25, 2013 by hgpu

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

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

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high performance computing on graphics processing units: hgpu.org

Applications

Efficient Implementation of MrBayes on multi-GPU

A dataflow-like programming model for future hybrid clusters

Exploring Different Automata Representations for Efficient Regular Expression Matching on GPUs

Warped Register File: A Power Efficient Register File for GPGPUs

Reaction-diffusion model Monte Carlo simulations on the GPU

GPUfs: Integrating a File System with GPUs

Advanced Trends of Heterogeneous Computing with CPU-GPU Integration: Comparative Study

Selection algorithm of graphic accelerators in heterogeneous cluster for optimization computing

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

Automatic Parallelization for GPUs

Orthogonalization on a General Purpose Graphics Processing Unit with Double Double and Quad Double Arithmetic

Regularization and nonlinearities for neural language models: when are they needed?

Recent source codes

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

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

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