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Fast heterogeneous computing with CUDA compatible Tesla GPU computing processor (personal supercomputing)

D. Kumar, M. A. Qadeer

Tags: Computer science, CUDA, Heterogeneous systems, Molecular dynamics, nVidia, Tesla

March 8, 2011 by hgpu

Performance and Scalability of GPU-Based Convolutional Neural Networks

Daniel Strigl, Klaus Kofler, Stefan Podlipnig

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Tags: Computer science, CUDA, Neural networks, nVidia

March 8, 2011 by hgpu

Offloading Region Matching of Data Distribution Management with CUDA

Shih Hsiang Lo, Yeh Ching Chung, Fang Ping Pai

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Tags: Computer science, CUDA, Distributed data structures, nVidia, nVidia GeForce 9600 GT

March 8, 2011 by hgpu

IP routing processing with graphic processors

Shuai Mu, Xinya Zhang, Nairen Zhang, Jiaxin Lu, Yangdong Steve Deng, Shu Zhang

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Tags: Bloom filter, Computer science, CUDA, Network communications, Networks, nVidia, nVidia GeForce GTX 280, Software router

March 7, 2011 by hgpu

Application-guided tool development for architecturally diverse computation

Roger D. Chamberlain, Jeremy Buhler, Mark A. Franklin, James H. Buckley

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Tags: Algorithms, Astrophysics, Biology, Computer science, CUDA, Finance, FPGA, Heterogeneous systems, Monte Carlo simulation, nVidia, nVidia GeForce GTX 260, Search, Security

March 7, 2011 by hgpu

Non-blocking programming on multi-core graphics processors: (extended asbtract)

Phuong Hoai Ha, Philippas Tsigas, Otto J. Anshus

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce 8800 GTX, Performance, Programming techniques

March 7, 2011 by hgpu

CUDA-based AES parallelization with fine-tuned GPU memory utilization

Chonglei Mei, Hai Jiang, Jeff Jenness

Tags: Computer science, CUDA, nVidia, Security

March 7, 2011 by hgpu

Designing scalable many-core parallel algorithms for min graphs using CUDA

Quoc-Nam Tran

Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia

March 7, 2011 by hgpu

Object-oriented stream programming using aspects

Mingliang Wang, M. Parashar

Tags: Computer science, CUDA, Hybrid computing, nVidia, nVidia GeForce GTX 280, Programming techniques

March 7, 2011 by hgpu

Object-oriented stream programming using Aspects: a high-productivity programming paradigm for hybrid platforms

Mingliang Wang

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Tags: Computer science, CUDA, Hybrid computing, nVidia, nVidia GeForce GTX 280, Programming techniques, Thesis

March 7, 2011 by hgpu

Dynamically tuned push-relabel algorithm for the maximum flow problem on CPU-GPU-Hybrid platforms

Zhengyu He, Bo Hong

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Tags: Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 285

March 6, 2011 by hgpu

Performance study of mapping irregular computations on GPUs

Steven Solomon, Parimala Thulasiraman

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Performance, Presentation

March 6, 2011 by hgpu

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

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

See all packages

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high performance computing on graphics processing units: hgpu.org

Fast heterogeneous computing with CUDA compatible Tesla GPU computing processor (personal supercomputing)

Performance and Scalability of GPU-Based Convolutional Neural Networks

Offloading Region Matching of Data Distribution Management with CUDA

IP routing processing with graphic processors

Application-guided tool development for architecturally diverse computation

Non-blocking programming on multi-core graphics processors: (extended asbtract)

CUDA-based AES parallelization with fine-tuned GPU memory utilization

Designing scalable many-core parallel algorithms for min graphs using CUDA

Object-oriented stream programming using aspects

Object-oriented stream programming using Aspects: a high-productivity programming paradigm for hybrid platforms

Dynamically tuned push-relabel algorithm for the maximum flow problem on CPU-GPU-Hybrid platforms

Performance study of mapping irregular computations on GPUs

Recent source codes

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

LLOR: Automatic Repair of OpenMP Programs

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