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RAPIDNN: In-Memory Deep Neural Network Acceleration Framework

Mohsen Imani, Mohammad Samragh, Yeseong Kim, Saransh Gupta, Farinaz Koushanfar, Tajana Rosing
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June 20, 2018 by hgpu

Dwarfs on Accelerators: Enhancing OpenCL Benchmarking for Heterogeneous Computing Architectures

Beau Johnston, Josh Milthorpe
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May 12, 2018 by hgpu

CANNA: Neural Network Acceleration using Configurable Approximation on GPGPU

Mohsen Imani, Max Masich, Daniel Peroni, Pushen Wang, Tajana Rosing
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April 22, 2018 by hgpu

Merge or Separate? Multi-job Scheduling for OpenCL Kernels on CPU/GPU Platforms

Yuan Wen, Michael F.P. O'Boyle
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April 3, 2017 by hgpu

Fast reconstruction of 3D volumes from 2D CT projection data with GPUs

M. Leeser, S. Mukherjee, J. Brock
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September 1, 2014 by hgpu

Recent source codes

OpenDwarfs: a benchmark suite consisting of different computation/communication idioms

OpenDwarfs: a benchmark suite consisting of different computation/communication idioms

Exploring FPGA-specific Optimizations for Irregular OpenCL Applications
Tango: A Deep Neural Network Benchmark Suite for Various Accelerators

Tango: A Deep Neural Network Benchmark Suite for Various Accelerators

Tango: A Deep Neural Network Benchmark Suite for Various Accelerators
MapD Core database

MapD Core database

Exact Selectivity Computation for Modern In-Memory Database Query Optimization
BitCracker: the first open source password cracking tool for memory units encrypted with BitLocker

BitCracker: the first open source password cracking tool for memory units encrypted with BitLocker

BitCracker: BitLocker meets GPUs
caffe-android-opencl-fp16: Optimised Caffe with OpenCL supporting for less powerful devices such as mobile phones

caffe-android-opencl-fp16: Optimised Caffe with OpenCL supporting for less powerful devices such as mobile phones

HG-Caffe: Mobile and Embedded Neural Network GPU (OpenCL) Inference Engine with FP16 Supporting
ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers
AutoParallel-Fortran: A domain specific, automatically parallelising source-to-source compiler for Fortran-95 that takes scientific Fortran as input and produces parallel Fortran/OpenCL

AutoParallel-Fortran: A domain specific, automatically parallelising source-to-source compiler for Fortran-95 that takes scientific Fortran as input and produces parallel Fortran/OpenCL

Towards Automatic Transformation of Legacy Scientific Code into OpenCL for Optimal Performance on FPGAs
gpussjoin: Set Similarity joins in the GPGPU paradigm

gpussjoin: Set Similarity joins in the GPGPU paradigm

Speeding-up the Verification Phase of Set Similarity Joins in the GPGPU paradigm
wav2letter: Facebook AI Research Automatic Speech Recognition Toolkit

wav2letter: Facebook AI Research Automatic Speech Recognition Toolkit

wav2letter++: The Fastest Open-source Speech Recognition System
GenASiS_Basics: Object-oriented Utilitarian Functionality for Large-scale Physics Simulations

GenASiS_Basics: Object-oriented Utilitarian Functionality for Large-scale Physics Simulations

Targeting GPUs with OpenMP Directives on Summit: A Simple and Effective Fortran Experience
See all packages

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