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Acceleration of Agent-Based Pandemic Modeling on Multiple GPUs

Barzan Shekh

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20, Thesis

November 25, 2015 by hgpu

Efficient Resource Sharing Through GPU Virtualization on Accelerated High Performance Computing Systems

Teng Li, Vikram K. Narayana, Tarek El-Ghazawi

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Tags: Computer science, CUDA, nVidia, Tesla C2070, Virtualization

November 25, 2015 by hgpu

Learning Representation for Scene Understanding: Epitomes, CRFs, and CNNs

Liang-Chieh Chen

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Source codes

Tags: Caffe, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 650 M, OpenCV, Tesla K40, Thesis

November 24, 2015 by hgpu

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Yong-Deok Kim, Eunhyeok Park, Sungjoo Yoo, Taelim Choi, Lu Yang, Dongjun Shin

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Tags: ARM, Bayesian, Caffe, CNN, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah

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Tags: Caffe, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures

E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, S. Rajamanickam

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Tags: Computer science, CUDA, Differential equations, nVidia, OpenMP, Partial differential equations, PDEs, Tesla K20

November 24, 2015 by hgpu

Recurrent Neural Networks Hardware Implementation on FPGA

Andre Xian Ming Chang, Berin Martini, Eugenio Culurciello

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Tags: ARM, Computer science, FPGA, Machine learning, Neural networks, nVidia, nVidia Jetson TK1

November 20, 2015 by hgpu

Supervised Hashing with Deep Neural Networks

Ziming Zhang, Yuting Chen, Venkatesh Saligrama

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Tags: Computer science, CUDA, Deep learning, Hashing, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan

November 20, 2015 by hgpu

Large Scale Artificial Neural Network Training Using Multi-GPUs

Linnan Wang, Wei Wu, Jianxiong Xiao, Yang Yi

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan X, Tesla K40

November 20, 2015 by hgpu

GPU-accelerated adjoint algorithmic differentiation

Felix Gremse, Andreas Hofter, Lukas Razik, Fabian Kiessling, Uwe Naumann

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, nVidia, nVidia GeForce GTX Titan Black, Tomography

November 20, 2015 by hgpu

GPU-Based Inverse Rendering With Multi-Objective Particle Swarm Optimization

Koki Nagano, Thomas Collins, Chi-An Chen, Aiichiro Nakano

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Tags: Algorithms, Computer science, GLSL, Particle swarm optimization, Rendering, Visualization

November 20, 2015 by hgpu

Fast Neuromimetic Object Recognition using FPGA Outperforms GPU Implementations

Garrick Orchard, Jacob G. Martin, R. Jacob Vogelstein, Ralph Etienne-Cummings

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Tags: Computer science, Computer vision, FPGA

November 13, 2015 by hgpu

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

HiRep

Scaling SU(2) to 1000 GPUs using HiRep

Gaia AVU-GSR

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Acceleration of Agent-Based Pandemic Modeling on Multiple GPUs

Efficient Resource Sharing Through GPU Virtualization on Accelerated High Performance Computing Systems

Learning Representation for Scene Understanding: Epitomes, CRFs, and CNNs

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures

Recurrent Neural Networks Hardware Implementation on FPGA

Supervised Hashing with Deep Neural Networks

Large Scale Artificial Neural Network Training Using Multi-GPUs

GPU-accelerated adjoint algorithmic differentiation

GPU-Based Inverse Rendering With Multi-Objective Particle Swarm Optimization

Fast Neuromimetic Object Recognition using FPGA Outperforms GPU Implementations

Recent source codes

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

SW#SYCL

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

HiRep

Gaia AVU-GSR

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

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