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Efficient Hardware Acceleration on SoC-FPGA with OpenCL

Susmitha Gogineni

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Tags: Computer science, Design space exploration, FPGA, Heterogeneous systems, HLS, OpenCL, Thesis

May 12, 2018 by hgpu

Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis

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Tags: Artificial intelligence, Computer science, Deep learning, Design space exploration, FPGA, OpenCL, survey

March 17, 2018 by hgpu

Analysing the Performance of GPU Hash Tables for State Space Exploration

Nathan Cassee, Anton Wijs

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Tags: Computer science, CUDA, Design space exploration, Hashing, nVidia, nVidia GeForce GT 750 M, Performance

January 6, 2018 by hgpu

Efficient Target and Application Specific Selection and Ordering of Compiler Passes

Ricardo Jorge Ferreira Nobre

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Tags: Code generation, Compilers, Computer science, CUDA, Design space exploration, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX 460, nVidia GeForce GTX 480, OpenCL, PTX, Thesis

November 26, 2017 by hgpu

Exploration of cyber-physical systems for GPGPU computer vision-based detection of biological viruses

Pascal Libuschewski

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Tags: Biology, Computer vision, Design space exploration, Microscopy, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 560 Ti, nVidia Quadro NVS 3100 M, OpenCL, Thesis, Visualization

April 20, 2017 by hgpu

Efficient Kernel Synthesis for Performance Portable Programming

Li-Wen Chang, Izzat El Hajj, Christopher Rodrigues, Juan Gomez-Luna, Wen-mei Hwu

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Tags: Code generation, Computer science, CUDA, Design space exploration, Heterogeneous systems, nVidia, performance portability, Tesla C2050, Tesla K20

November 25, 2016 by hgpu

Many-Core Architectures: Hardware-Software Optimization and Modeling Techniques

Christian Pinto

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Tags: Computer science, CUDA, Design space exploration, nVidia, nVidia GeForce GTX 480, Thesis, Virtualization

July 17, 2015 by hgpu

Flexible Software Profiling of GPU Architectures

Mark Stephenson, Siva Kumar Sastry Hari, Yunsup Lee, Eiman Ebrahimi, Daniel R. Johnson, David Nellans, Mike O'Connor, Stephen W. Keckler

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Tags: Computer science, CUDA, Design space exploration, nVidia, PTX, Tesla K10, Tesla K20, Tesla K40

April 25, 2015 by hgpu

Design Space Exploration of OpenCL Applications on Heterogeneous Parallel Platforms

Edoardo Paone

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Tags: Computer science, CUDA, Design space exploration, Heterogeneous systems, nVidia, nVidia Quadro NVS 300, OpenCL, Thesis

January 30, 2015 by hgpu

Hierarchical Mapping Techniques for Signal Processing Systems on Parallel Platforms

Lai-Huei Wang

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Tags: Computer vision, CUDA, Design space exploration, DSP, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 680, Signal processing, Thesis

October 31, 2014 by hgpu

An Energy Optimization of a GPU Application by Grid Design Space Exploration

Hana Park, Jungmin So, Young-Woong Ko, Jeong-Gun Lee

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Tags: Computer science, CUDA, Design space exploration, Energy-efficient computing, nVidia, nVidia GeForce GTX 660

August 8, 2013 by hgpu

Starchart: Hardware and Software Optimization Using Recursive Partitioning Regression Trees

Wenhao Jia, Kelly A. Shaw, Margaret Martonosi

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Design space exploration, nVidia, OpenCL, Tesla C2070

July 17, 2013 by hgpu

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

MyCaffe: A Complete C# Re-Write of Caffe with Reinforcement Learning

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

CL-kmeans: Efficient k-Means in OpenCL

Efficient and Scalable k-Means on GPUs

Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

pyJac: a Python package that generates source code used to analytically calculate chemical kinetics Jacobian matrices

Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms

CUTLASS: CUDA Templates for Linear Algebra Subroutines

Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs

Integer sorting on multicore

A study of integer sorting on multicores

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10-12

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high performance computing on graphics processing units: hgpu.org

Efficient Hardware Acceleration on SoC-FPGA with OpenCL

Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

Analysing the Performance of GPU Hash Tables for State Space Exploration

Efficient Target and Application Specific Selection and Ordering of Compiler Passes

Exploration of cyber-physical systems for GPGPU computer vision-based detection of biological viruses

Efficient Kernel Synthesis for Performance Portable Programming

Many-Core Architectures: Hardware-Software Optimization and Modeling Techniques

Flexible Software Profiling of GPU Architectures

Design Space Exploration of OpenCL Applications on Heterogeneous Parallel Platforms

Hierarchical Mapping Techniques for Signal Processing Systems on Parallel Platforms

An Energy Optimization of a GPU Application by Grid Design Space Exploration

Starchart: Hardware and Software Optimization Using Recursive Partitioning Regression Trees

Recent source codes

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

CL-kmeans: Efficient k-Means in OpenCL

Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

pyJac: a Python package that generates source code used to analytically calculate chemical kinetics Jacobian matrices

CUTLASS: CUDA Templates for Linear Algebra Subroutines

Integer sorting on multicore

Most viewed papers (last 30 days)

Featured events

International Conference on Image, Video and Signal Processing (IVSP), 2019

International Joint Conference on Signals, Systems and Computers (CSSC), 2018

International Joint Conference on Robotics, Automation and Mechatronics (JCRAM), 2018

International Joint Conference on Robotics and Artificial Intelligence (JCRAI), 2018

International Joint Conference on Computer Vision and Pattern Recognition (CCVPR), 2018