high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » paper

Model-independent partial wave analysis using a massively-parallel fitting framework

Liang Sun, Rafael Aoude, Alberto Correa Dos Reis, Michael David Sokoloff

View

Download (PDF)

Source codes

Tags: Algorithms, CUDA, High Energy Physics - Experiment, nVidia, OpenMP, Package, Physics, Tesla K40

March 14, 2017 by hgpu

A Survey of Cache Partitioning Techniques for Multicore Processors

Sparsh Mittal

View

Download (PDF)

Tags: cache partitioning, computer architecture, Multicore processors, Power management, shared cache

March 10, 2017 by sparsh0mittal

Architectural Principles and Experimentation of Distributed High Performance Virtual Clusters

Andrew J. Younge

View

Download (PDF)

Tags: Cloud, Computer science, CUDA, Distributed computing, Molecular dynamics, nVidia, OpenCL, Tesla C2075, Tesla K20, Thesis, Virtualization

March 9, 2017 by hgpu

Achieving high-performance with a sparse direct solver on Intel KNL

Emmanuel Agullo, Alfredo Buttari, Mikko Byckling, Abdou Guermouche, Ian Masliah

View

Download (PDF)

Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Sparse direct solvers

March 9, 2017 by hgpu

Optimizing Deep CNN-Based Queries over Video Streams at Scale

Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, Matei Zaharia

View

Download (PDF)

Source codes

Tags: Computer science, Computer vision, Databases, Deep learning, Machine learning, Neural networks, nVidia, nVidia DGX-1, Package, TensorFlow, Tesla P100

March 9, 2017 by hgpu

A Machine-Learning Framework for Design for Manufacturability

Aditya Balu, Sambit Ghadai, Gavin Young, Soumik Sarkar, Adarsh Krishnamurthy

View

Download (PDF)

Tags: CNN, Computer science, Deep learning, Keras, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia Quadro K 2200

March 9, 2017 by hgpu

Decoupled Block-Wise ILU(k) Preconditioner on GPU

Bo Yang, Hui Liu, He Zhong, Zhangxin Chen

View

Download (PDF)

Tags: Computer science, CUDA, Factorization, nVidia, Sparse matrix, Tesla K20

March 9, 2017 by hgpu

Wireless Interference Identification with Convolutional Neural Networks

Malte Schmidt, Dimitri Block, Uwe Meier

View

Download (PDF)

Tags: CNN, Deep learning, Keras, Neural networks, nVidia, nVidia GeForce GTX 960, Signal processing

March 5, 2017 by hgpu

Multi-kernel Data Partitioning with Channel on OpenCL-based FPGAs

Zeke Wang, Johns Paul, Bingsheng He, Wei Zhang

View

Download (PDF)

Tags: Computer science, Databases, FPGA, OpenCL, Performance

March 5, 2017 by hgpu

Improving the Neural GPU Architecture for Algorithm Learning

Karlis Freivalds, Renars Liepins

View

Download (PDF)

Source codes

Tags: Algorithms, Artificial intelligence, Computer science, Deep learning, Memory model, nVidia, Package, Python, TensorFlow, Tesla K40

March 5, 2017 by hgpu

Performance and Portability of Accelerated Lattice Boltzmann Applications with OpenACC

E. Calore, A. Gabbana, J. Kraus, S. F. Schifano, R. Tripiccione

View

Download (PDF)

Tags: AMD FirePro S9150, ATI, Benchmarking, CUDA, Fluid dynamics, Lattice Boltzmann model, MPI, nVidia, OpenACC, OpenCL, Performance, Tesla K80

March 5, 2017 by hgpu

Billion-scale similarity search with GPUs

Jeff Johnson, Matthijs Douze, Herve Jegou

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Data Structures and Algorithms, Databases, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan X, Package

March 5, 2017 by hgpu

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Model-independent partial wave analysis using a massively-parallel fitting framework

A Survey of Cache Partitioning Techniques for Multicore Processors

Achieving high-performance with a sparse direct solver on Intel KNL

Optimizing Deep CNN-Based Queries over Video Streams at Scale

A Machine-Learning Framework for Design for Manufacturability

Decoupled Block-Wise ILU(k) Preconditioner on GPU

Wireless Interference Identification with Convolutional Neural Networks

Multi-kernel Data Partitioning with Channel on OpenCL-based FPGAs

Improving the Neural GPU Architecture for Algorithm Learning

Performance and Portability of Accelerated Lattice Boltzmann Applications with OpenACC

Billion-scale similarity search with GPUs

Recent source codes

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

Most viewed papers (last 30 days)