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Minerva: A Scalable and Highly Efficient Training Platform for Deep Learning

Minjie Wang, Tianjun Xiao, Jianpeng Li, Jiaxing Zhang, Chuntao Hong, Zheng Zhang

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Tags: Computer science, CUBLAS, CUDA, Machine learning, Neural networks, nVidia

December 15, 2014 by hgpu

Bayesian neural networks for detecting epistasis in genetic association studies

Andrew L Beam, Alison Motsinger-Reif, Jon Doyle

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Tags: Bayesian, Biology, CUDA, CULA, Neural networks, nVidia, Package, Python

December 15, 2014 by hgpu

Analysis and Optimization Techniques for Massively Parallel Processors

Wenhao Jia

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, PTX, Tesla C2070, Thesis, Virtualization

December 15, 2014 by hgpu

Easy-to-Use On-the-Fly Binary Program Acceleration on Many-Cores

Marvin Damschen, Christian Plessl

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Tags: Computer science, Intel Xeon Phi, Package, Performance

December 15, 2014 by hgpu

Performance Comparison of GPUs with a Genetic Algorithm based on CUDA

Jae-Hyun Seo, Eun-Sol Ko, Yong-Hyuk Kim

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Tags: Algorithms, Computer science, CUDA, Genetic algorithm, nVidia, nVidia GeForce GT 430, nVidia GeForce GTX 260, nVidia GeForce GTX 760, nVidia GeForce GTX 770

December 15, 2014 by hgpu

Bamboo: Automatic Translation of MPI Source into a Latency-Tolerant Form

Nhat Tan Nguyen Thanh

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Tags: Computer science, CUDA, Linear Algebra, MPI, nVidia, Package, Tesla K20, Thesis

December 15, 2014 by hgpu

Heuristics for Conversion Process of GPU’s Kernels for Multiples Kernels with Concurrent Optimization Divergence

Jose Ritomar Carneiro Torquato, Esteban Walter Gonzalez Clua

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Performance, Tesla K10, Tesla K20

December 14, 2014 by hgpu

Locality-Aware Automatic Parallelization for GPGPU with OpenHMPP Directives

Jose M. Andion, Manuel Arenaz, Francois Bodin, Gabriel Rodriguez, Juan Tourino

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Tags: Computer science, CUDA, Heterogeneous systems, Matrix multiplication, nVidia, Tesla S1070, Tesla S2050

December 14, 2014 by hgpu

Acceleration of Hessenberg Reduction for Nonsymmetric Matrix

Hesamaldin Nekouei

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Tags: Algorithms, Computer science, CUDA, FFT, Linear Algebra, nVidia, nVidia GeForce GT 635 M, Thesis

December 14, 2014 by hgpu

Graph Processing on GPU

Zhang Jingbo

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Tags: Algorithms, Computer science, CUDA, Data mining, Graph theory, Machine learning, nVidia, nVidia GeForce 9400 GT, nVidia GeForce GT 330, nVidia GeForce GT 520, Thesis

December 14, 2014 by hgpu

C++ AMP: Accelerated Massive Parallelism with Microsoft Visual C++

Kate Gregory, Ade Miller

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Tags: Book, C++ AMP, Programming Languages

December 13, 2014 by AlexVlx

Real-Time Grasp Detection Using Convolutional Neural Networks

Joseph Redmon, Anelia Angelova

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Tags: CNN, Computer science, CUDA, Machine learning, Neural networks, nVidia, Tesla K20

December 12, 2014 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

Minerva: A Scalable and Highly Efficient Training Platform for Deep Learning

Bayesian neural networks for detecting epistasis in genetic association studies

Analysis and Optimization Techniques for Massively Parallel Processors

Easy-to-Use On-the-Fly Binary Program Acceleration on Many-Cores

Performance Comparison of GPUs with a Genetic Algorithm based on CUDA

Bamboo: Automatic Translation of MPI Source into a Latency-Tolerant Form

Heuristics for Conversion Process of GPU’s Kernels for Multiples Kernels with Concurrent Optimization Divergence

Locality-Aware Automatic Parallelization for GPGPU with OpenHMPP Directives

Acceleration of Hessenberg Reduction for Nonsymmetric Matrix

Graph Processing on GPU

C++ AMP: Accelerated Massive Parallelism with Microsoft Visual C++

Real-Time Grasp Detection Using Convolutional Neural Networks

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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