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BENCHIP: Benchmarking Intelligence Processors

Jin-Hua Tao, Zi-Dong Du, Qi Guo, Hui-Ying Lan, Lei Zhang, Sheng-Yuan Zhou, Cong Liu, Hai-Feng Liu, Shan Tang, Allen Rush, Willian Chen, Shao-Li Liu, Yun-Ji Chen, Tian-Shi Chen

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Tags: ASIC, Benchmarking, Computer science, Deep learning, nVidia, nVidia GeForce GTX 950, nVidia Tegra TX1, Tesla K40

October 24, 2017 by hgpu

Evaluation of GPU-based track-triggering for the CMS detector at CERN’s HL-LHC

Hannes Mohr

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Tags: Algorithms, ASIC, CUDA, FPGA, HEP, nVidia, Physics, Tesla K40, Tesla K80, Thesis

April 20, 2017 by hgpu

Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC

Eriko Nurvitadhi, David Sheffield, Jaewoong Sim, Asit Mishra, Ganesh Venkatesh, Debbie Marr

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Tags: Algorithms, ASIC, Computer science, CUDA, Deep learning, FPGA, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1, Performance

February 14, 2017 by hgpu

SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing

Ao Ren, Ji Li, Zhe Li, Caiwen Ding, Xuehai Qian, Qinru Qiu, Bo Yuan, Yanzhi Wang

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Tags: ASIC, CNN, Computer science, Deep learning, FPGA, Neural networks, nVidia, Tesla C2075

November 22, 2016 by hgpu

Runtime Configurable Deep Neural Networks for Energy-Accuracy Trade-off

Hokchhay Tann, Soheil Hashemi, R. Iris Bahar, Sherief Reda

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Tags: Algorithms, ARM, ASIC, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia Tegra TX1

July 20, 2016 by hgpu

Hardware Acceleration for Unstructured Big Data and Natural Language Processing

Prateek Tandon

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Tags: ASIC, big data, Computer science, FPGA, Hadoop, hardware acceleration, Machine learning, MapReduce, NLP, Thesis

February 2, 2016 by hgpu

Origami: A Convolutional Network Accelerator

Lukas Cavigelli, David Gschwend, Christoph Mayer, Samuel Willi, Beat Muheim, Luca Benini

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Tags: Algorithms, Artificial intelligence, ASIC, Computer science, Computer vision, Machine learning, Neural networks

December 15, 2015 by hgpu

TABLA: A Unified Template-based Framework for Accelerating Statistical Machine Learning

Divya Mahajan, Jongse Park, Emmanuel Amaro, Hardik Sharma, Amir Yazdanbakhsh, Joon Kim, Hadi Esmaeilzadeh

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Tags: ARM, ASIC, Computer science, FPGA, Machine learning, nVidia, nVidia GeForce GTX 650 Ti, nVidia Jetson TK1, Performance, Tesla K40

September 29, 2015 by hgpu

RadixBoost: A Hardware Acceleration Structure for Scalable Radix Sort on Graphic Processors

Xingyu Liu, Shikai Li, Kuan Fang, Yufei Ni, Zonghui Li, Yangdong Deng

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Tags: Algorithms, ASIC, Computer science, FPGA, nVidia, nVidia GeForce GTX 580, Sorting

March 12, 2015 by hgpu

FastTree: A Hardware KD-Tree Construction Acceleration Engine for Real-Time Ray Tracing

Xingyu Liu, Yangdong Deng, Yufei Ni, Zonghui Li

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Tags: Algorithms, ASIC, Computer science, FPGA, KD-tree, Raytracing, Rendering

March 12, 2015 by hgpu

FPGA Acceleration of Multifunction Printer Image Processing using OpenCL

Timothy M. Hunter, Dmitry Denisenko, Sarnath Kannan, Jared M. Bold, Prasanthi Thippabathini, Peter Dusel P.E.

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Tags: ASIC, FPGA, Image processing, OpenCL

August 5, 2014 by hgpu

Bitcoin and The Age of Bespoke Silicon

Michael Bedford Taylor

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Tags: ASIC, ATI, Finance, FPGA, nVidia, OpenCL, Performance, Review

August 31, 2013 by hgpu

Neural Query Language: A Knowledge Base Query Language for Tensorflow

TensorNetwork: A TensorFlow library for easy and efficient manipulation of tensor networks

TensorNetwork: A Library for Physics and Machine Learning

jive

Principles, Techniques, and Tools for Explicit and Automatic Parallelization

caffe-mc-opencl: Caffe Deep Learning Software with Model Compression by Sparse Coding (Backend: OpenCL)

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems

Full-stack Optimization for Accelerating CNNs with FPGA Validation

AdaNet: Fast and flexible AutoML with learning guarantees

AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles

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2019

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13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019

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high performance computing on graphics processing units: hgpu.org

BENCHIP: Benchmarking Intelligence Processors

Evaluation of GPU-based track-triggering for the CMS detector at CERN’s HL-LHC

Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC

SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing

Runtime Configurable Deep Neural Networks for Energy-Accuracy Trade-off

Hardware Acceleration for Unstructured Big Data and Natural Language Processing

Origami: A Convolutional Network Accelerator

TABLA: A Unified Template-based Framework for Accelerating Statistical Machine Learning

RadixBoost: A Hardware Acceleration Structure for Scalable Radix Sort on Graphic Processors

FastTree: A Hardware KD-Tree Construction Acceleration Engine for Real-Time Ray Tracing

FPGA Acceleration of Multifunction Printer Image Processing using OpenCL

Bitcoin and The Age of Bespoke Silicon

Recent source codes

Neural Query Language: A Knowledge Base Query Language for Tensorflow

NMODL: Code Generation Framework For NEURON MODeling Language

TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox

cuda-benches: collection of small CUDA benchmarking programs

Simulee: Charactering and Detecting CUDA Program Bugs

TensorNetwork: A TensorFlow library for easy and efficient manipulation of tensor networks

jive

caffe-mc-opencl: Caffe Deep Learning Software with Model Compression by Sparse Coding (Backend: OpenCL)

Full-stack Optimization for Accelerating CNNs with FPGA Validation

AdaNet: Fast and flexible AutoML with learning guarantees

Most viewed papers (last 30 days)

Featured events

7th International Workshop on OpenCL, 2019

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

International Conference on Frontiers of Neural Networks (ICFNN), 2019

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019