high performance computing on graphics processing units: hgpu.org

hgpu.org » Tesla K40

Accelerated dimension-independent adaptive Metropolis

Yuxin Chen, David Keyes, Kody J.H. Law, Hatem Ltaief

View

Download (PDF)

Tags: CUDA, nVidia, Probability, Statistics, Tesla K40

June 19, 2015 by hgpu

Exploring the Suitability of Remote GPGPU Virtualization for the OpenACC Programming Model Using rCUDA

Adrian Castello, Rafael Mayo, Enrique S. Quintana-Orti, Antonio J. Pena, Pavan Balaji

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Tesla C2050, Tesla K40, Virtualization

June 17, 2015 by hgpu

Layered Interpretation of Street View Images

Ming-Yu Liu, Shuoxin Lin, Srikumar Ramalingam, Oncel Tuzel

View

Download (PDF)

Tags: Algorithms, Computer science, Computer vision, CUDA, Neural networks, nVidia, Robotics, Tesla K40, Vehicular traffic

June 17, 2015 by hgpu

Characterizing Dataset Dependence for Sparse Matrix-Vector Multiplication on GPUs

N. Sedaghati, A. Ashari, L. N. Pouchet, S. Parthasarathy, P. Sadayappan

View

Download (PDF)

Tags: Computer science, CUDA, Linear Algebra, nVidia, Performance, Sparse matrix, Tesla K40

June 16, 2015 by hgpu

Type-safe Runtime Code Generation: Accelerate to LLVM

Trevor L. McDonell, Manuel M. T. Chakravarty, Vinod Grover, Ryan R. Newton

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, nVidia, Package, Sparse matrix, Tesla K40

June 14, 2015 by hgpu

Automatic Selection of Sparse Matrix Representation on GPUs

Naser Sedaghati, Te Mu, Louis-Noel Pouchet, Srinivasan Parthasarathy, P. Sadayappan

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 580, Physics, Sparse matrix, Tesla K20, Tesla K40

June 14, 2015 by hgpu

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun

View

Download (PDF)

Source codes

Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, Package, Tesla K40

June 7, 2015 by hgpu

Meta-Programming and Auto-Tuning in the Search for High Performance GPU Code

Michael Vollmer, Bo Joel Svensson, Eric Holk, Ryan Newton

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Performance, Search strategies, Tesla K40

June 7, 2015 by hgpu

Machine Learning Based Auto-tuning for Enhanced OpenCL Performance Portability

Thomas L. Falch, Anne C. Elster

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7970, Benchmarking, Computer science, Deep learning, Heterogeneous systems, Machine learning, Neural networks, nVidia, OpenCL, Tesla K40

June 5, 2015 by hgpu

Accelerated Nodal Discontinuous Galerkin Simulations for Reverse Time Migration with Large Clusters

Axel Modave, Amik St-Cyr, Wim A. Mulder, Tim Warburton

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7970, Computational Physics, CUDA, Geophysics, MPI, nVidia, nVidia GeForce GTX 980, OpenCL, Physics, Tesla K20, Tesla K40

June 5, 2015 by hgpu

Genetically Improved BarraCUDA

W. B. Langdon, Brian Yee Hong Lam

View

Download (PDF)

Source codes

Tags: Algorithms, Benchmarking, Biology, CUDA, Genomics, nVidia, nVidia GeForce GT 730, Package, Tesla K20, Tesla K40, Tesla K80

June 1, 2015 by hgpu

DjiNN and Tonic: DNN as a Service and Its Implications for Future Warehouse Scale Computers

Johann Hauswald, Yiping Kang, Michael A. Laurenzano, Quan Chen, Cheng Li, Trevor Mudge, Ronald G. Dreslinski, Jason Mars, Lingjia Tang

View

Download (PDF)

Tags: CUDA, Deep learning, Image processing, Machine learning, Neural networks, nVidia, Speech recognition, Tesla K40

May 25, 2015 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

Accelerated dimension-independent adaptive Metropolis

Exploring the Suitability of Remote GPGPU Virtualization for the OpenACC Programming Model Using rCUDA

Layered Interpretation of Street View Images

Characterizing Dataset Dependence for Sparse Matrix-Vector Multiplication on GPUs

Type-safe Runtime Code Generation: Accelerate to LLVM

Automatic Selection of Sparse Matrix Representation on GPUs

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Meta-Programming and Auto-Tuning in the Search for High Performance GPU Code

Machine Learning Based Auto-tuning for Enhanced OpenCL Performance Portability

Accelerated Nodal Discontinuous Galerkin Simulations for Reverse Time Migration with Large Clusters

Genetically Improved BarraCUDA

DjiNN and Tonic: DNN as a Service and Its Implications for Future Warehouse Scale Computers

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)