paper | Page 134 | hgpu.org

Applications

hgpu.org » paper

ARC: Adaptive Ray-tracing with CUDA, a New Ray Tracing Code for Parallel GPUs

Blake Hartley, Massimo Ricotti

View

Download (PDF)

Tags: Astrophysics, Cosmology, CUDA, MPI, nVidia, Raytracing

July 21, 2018 by hgpu

LeFlow: Enabling Flexible FPGA High-Level Synthesis of Tensorflow Deep Neural Networks

Daniel H. Noronha, Bahar Salehpour, Steven J.E. Wilton

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, FPGA, LSTM, Machine learning, Neural networks, Package, Python, TensorFlow

July 21, 2018 by hgpu

Cross-Compiling Shading Languages

Lukas Hermanns

View

Download (PDF)

Tags: 3D Graphics and Realism, Algorithms, DirectX, GLSL, HLSL, OpenGL, Real-time graphics, Rendering, Thesis

July 15, 2018 by hgpu

Revisiting Online Autotuning for Sparse-Matrix Vector Multiplication Kernels on High-Performance Accelerators

Simon Garcia De Gonzalo, Wen-Mei Hwu, Simon D. Hammond, Christian R. Trott

View

Download (PDF)

Tags: Computer science, Intel Xeon Phi, nVidia, Performance, Sparse matrix, Tesla P100

July 15, 2018 by hgpu

Multicore architecture and cache optimization techniques for solving graph problems

Alvaro Tzul

View

Download (PDF)

Tags: Computer science, CUDA, Graph theory, nVidia

July 15, 2018 by hgpu

CloudCL: Single-Paradigm Distributed Heterogeneous Computing for Cloud Infrastructures

Max Plauth, Florian Roesler, Andreas Polze

View

Download (PDF)

Source codes

Tags: Cloud, Computer science, Java, MPI, nVidia, nVidia GRID K520, OpenCL, Package

July 15, 2018 by hgpu

Data-Parallel Hashing Techniques for GPU Architectures

Brenton Lessley

View

Download (PDF)

Tags: Computer science, CUDA, Hashing, nVidia

July 15, 2018 by hgpu

Application of Deep-Learning to Compiler-Based Graphs

Tristan Vanderbruggen

View

Download (PDF)

Tags: Compilers, Computer science, Deep learning, Graph theory, Machine learning, Neural networks, nVidia, nVidia GRID K520, OpenCL, Thesis

July 7, 2018 by hgpu

Calamari – A High-Performance Tensorflow-based Deep Learning Package for Optical Character Recognition

Christoph Wick, Christian Reul, Frank Puppe

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, Package, Python, TensorFlow

July 7, 2018 by hgpu

Energy Consumption of Algorithms for Solving the Compressible Navier-Stokes Equations on CPU’s, GPU’s and KNL’s

Satya P. Jammy, Christian T. Jacobs, David J. Lusher, Neil D. Sandham

View

Download (PDF)

Tags: CUDA, Finite difference, Fluid dynamics, Intel Xeon Phi, Navier-Stokes equations, NSEs, nVidia, Tesla K40

July 7, 2018 by hgpu

FluidFFT: common API (C++ and Python) for Fast Fourier Transform HPC libraries

Ashwin Vishnu Mohanan, Cyrille Bonamy, Pierre Augier

View

Download (PDF)

Source codes

Tags: Benchmarking, cfd, CUDA, FFT, Fluid dynamics, MPI, Package, Python

July 7, 2018 by hgpu

An Efficient Dispatcher for Large Scale GraphProcessing on OpenCL-based FPGAs

Chengbo Yang

View

Download (PDF)

Tags: Computer science, FPGA, Graph theory, OpenCL, Task scheduling

July 7, 2018 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

ARC: Adaptive Ray-tracing with CUDA, a New Ray Tracing Code for Parallel GPUs

LeFlow: Enabling Flexible FPGA High-Level Synthesis of Tensorflow Deep Neural Networks

Cross-Compiling Shading Languages

Revisiting Online Autotuning for Sparse-Matrix Vector Multiplication Kernels on High-Performance Accelerators

Multicore architecture and cache optimization techniques for solving graph problems

Data-Parallel Hashing Techniques for GPU Architectures

Application of Deep-Learning to Compiler-Based Graphs

Calamari – A High-Performance Tensorflow-based Deep Learning Package for Optical Character Recognition

Energy Consumption of Algorithms for Solving the Compressible Navier-Stokes Equations on CPU’s, GPU’s and KNL’s

FluidFFT: common API (C++ and Python) for Fast Fourier Transform HPC libraries

An Efficient Dispatcher for Large Scale GraphProcessing on OpenCL-based FPGAs

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)