18288
hgpu.org » AMD Radeon HD 7970

RAPIDNN: In-Memory Deep Neural Network Acceleration Framework

Mohsen Imani, Mohammad Samragh, Yeseong Kim, Saransh Gupta, Farinaz Koushanfar, Tajana Rosing
View View   Download Download (PDF)   

Tags: , , , , , , , ,

June 20, 2018 by hgpu

Dwarfs on Accelerators: Enhancing OpenCL Benchmarking for Heterogeneous Computing Architectures

Beau Johnston, Josh Milthorpe
View View   Download Download (PDF)   

Tags: , , , , , , , , , , , , , ,

May 12, 2018 by hgpu

CANNA: Neural Network Acceleration using Configurable Approximation on GPGPU

Mohsen Imani, Max Masich, Daniel Peroni, Pushen Wang, Tajana Rosing
View View   Download Download (PDF)   

Tags: , , , , ,

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
View View   Download Download (PDF)   

Tags: , , , , , , ,

April 3, 2017 by hgpu

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

M. Leeser, S. Mukherjee, J. Brock
View View   Download Download (PDF)   

Tags: , , , , , , , , ,

September 1, 2014 by hgpu

Recent source codes

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

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

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

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

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications
CL-kmeans: Efficient k-Means in OpenCL

CL-kmeans: Efficient k-Means in OpenCL

Efficient and Scalable k-Means on GPUs
Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

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

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

CUTLASS: CUDA Templates for Linear Algebra Subroutines

Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs
Integer sorting on multicore

Integer sorting on multicore

A study of integer sorting on multicores
Kernel Tuner: A search-optimizing GPU code auto-tuner

Kernel Tuner: A search-optimizing GPU code auto-tuner

Kernel Tuner: A search-optimizing GPU code auto-tuner
libxsmm: Library targeting Intel Architecture for specialized dense and sparse matrix operations, and deep learning primitives

libxsmm: Library targeting Intel Architecture for specialized dense and sparse matrix operations, and deep learning primitives

Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures
See all packages

* * *

* * *

HGPU group © 2010-2018 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: