high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Accelerating Blockchain Search of Full Nodes Using GPUs

Shin Morishima, Hiroki Matsutani

View

Download (PDF)

Tags: Computer science, CUDA, Finance, nVidia, nVidia GeForce GTX 980 Ti

April 28, 2018 by hgpu

Automatic generation of CUDA code performing tensor manipulations using C++ expression templates

Adam G.M. Lewis, Harald P. Pfeiffer

View

Download (PDF)

Tags: Benchmarking, Code generation, Computer science, CUDA, General Relativity and Quantum Cosmology, nVidia, Tesla K80, Tesla M2090, Tesla P100

April 28, 2018 by hgpu

BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism

Nicolas Weber, Florian Schmidt, Mathias Niepert, Felipe Huici

View

Download (PDF)

Tags: AI, Artificial intelligence, cache, CNN, Computer science, cpu, CUDA, Deep learning, GPU, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 1080 Ti

April 25, 2018 by hgpu

CANNA: Neural Network Acceleration using Configurable Approximation on GPGPU

Mohsen Imani, Max Masich, Daniel Peroni, Pushen Wang, Tajana Rosing

View

Download (PDF)

Tags: AMD Radeon HD 7970, ATI, Computer science, Deep learning, Neural networks, OpenCL

April 22, 2018 by hgpu

CytonRL: an Efficient Reinforcement Learning Open-source Toolkit Implemented in C++

Xiaolin Wang

View

Download (PDF)

Source codes

Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, OpenCV, Package

April 22, 2018 by hgpu

mu-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching

Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka

View

Download (PDF)

Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, Tesla P100

April 22, 2018 by hgpu

Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking

Zhe Jia, Marco Maggioni, Benjamin Staiger, Daniele P. Scarpazza

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, nVidia, Performance, PTX, Tesla V100

April 22, 2018 by hgpu

DLL: A Blazing Fast Deep Neural Network Library

Baptiste Wicht, Jean Hennebert, Andreas Fischer

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 960, Package, Software Engineering

April 15, 2018 by hgpu

Automatic Optimization of OpenCL-Based Stencil Codes for FPGAs and Its Evaluation

Tsukasa Endo, Hasitha Muthumala Waidyasooriya, Masanori Hariyama

View

Download (PDF)

Tags: Computer science, FPGA, OpenCL, Performance, Stencil computation

April 15, 2018 by hgpu

Implementing Push-Pull Efficiently in GraphBLAS

Carl Yang, Aydin Buluc, John D. Owens

View

Download (PDF)

Tags: Algorithm optimization, Algorithms, BLAS, Computer science, CUDA, Graph theory, Linear Algebra, nVidia, Sparse matrix, Tesla K40

April 15, 2018 by hgpu

G-NET: Effective GPU Sharing in NFV Systems

Kai Zhang, Bingsheng He, Jiayu Hu, Zeke Wang, Bei Hua, Jiayi Meng, Lishan Yang

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, Virtualization

April 15, 2018 by hgpu

Towards a Unified CPU-GPU code hybridization: A GPU Based Optimization Strategy Efficient on Other Modern Architectures

Ludomir Oteski, Guillaume De Verdiere, Sylvain Contassot-Vivier, Stephane Vialle, Juliet Ryan

View

Download (PDF)

Tags: Computer science, CUDA, Fluid dynamics, Intel Xeon Phi, nVidia, Tesla K20, Tesla P100

April 15, 2018 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Programming

Accelerating Blockchain Search of Full Nodes Using GPUs

Automatic generation of CUDA code performing tensor manipulations using C++ expression templates

BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism

CANNA: Neural Network Acceleration using Configurable Approximation on GPGPU

CytonRL: an Efficient Reinforcement Learning Open-source Toolkit Implemented in C++

mu-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching

Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking

DLL: A Blazing Fast Deep Neural Network Library

Automatic Optimization of OpenCL-Based Stencil Codes for FPGAs and Its Evaluation

Implementing Push-Pull Efficiently in GraphBLAS

G-NET: Effective GPU Sharing in NFV Systems

Towards a Unified CPU-GPU code hybridization: A GPU Based Optimization Strategy Efficient on Other Modern Architectures

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Most viewed papers (last 30 days)