high performance computing on graphics processing units: hgpu.org

hgpu.org » Design space exploration

Performance Debugging Frameworks for FPGA High-Level Synthesis

Young-kyu Choi

View

Tags: Benchmarking, Computer science, Design space exploration, FPGA, HLS, Performance, Thesis

October 27, 2019 by hgpu

Fast Code Exploration for Pipeline Processing in FPGA Accelerators

Leandro de Souza Rosa

View

Tags: Computer science, Design space exploration, FPGA, HLS, Thesis

September 8, 2019 by hgpu

Compilers for Portable Programming of Heterogeneous Parallel & Approximate Computing Systems

Prakalp Srivastava

View

Tags: Code generation, Computer science, Design space exploration, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL, performance portability

September 8, 2019 by hgpu

High Performance Computing via High Level Synthesis

Mehdi Roozmeh

View

Tags: Computer science, Design space exploration, FPGA, Heterogeneous systems, HLS, Nearest neighbour, nVidia, OpenCL, Package, Signal processing, Thesis

August 18, 2019 by hgpu

Software Platform for Hybrid Resource Management of Many-core Accelerators

Taeyoung Kim

View

Tags: Computer science, Design space exploration, Intel Xeon Phi, OpenCL, Thesis

December 16, 2018 by hgpu

Efficient Hardware Acceleration on SoC-FPGA with OpenCL

Susmitha Gogineni

View

Tags: Computer science, Design space exploration, FPGA, Heterogeneous systems, HLS, OpenCL, Thesis

May 12, 2018 by hgpu

Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis

View

Tags: Artificial intelligence, Computer science, Deep learning, Design space exploration, FPGA, OpenCL, survey

March 17, 2018 by hgpu

Analysing the Performance of GPU Hash Tables for State Space Exploration

Nathan Cassee, Anton Wijs

View

Tags: Computer science, CUDA, Design space exploration, Hashing, nVidia, nVidia GeForce GT 750 M, Performance

January 6, 2018 by hgpu

Efficient Target and Application Specific Selection and Ordering of Compiler Passes

Ricardo Jorge Ferreira Nobre

View

Tags: Code generation, Compilers, Computer science, CUDA, Design space exploration, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX 460, nVidia GeForce GTX 480, OpenCL, PTX, Thesis

November 26, 2017 by hgpu

Exploration of cyber-physical systems for GPGPU computer vision-based detection of biological viruses

Pascal Libuschewski

View

Tags: Biology, Computer vision, Design space exploration, Microscopy, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 560 Ti, nVidia Quadro NVS 3100 M, OpenCL, Thesis, Visualization

April 20, 2017 by hgpu

Efficient Kernel Synthesis for Performance Portable Programming

Li-Wen Chang, Izzat El Hajj, Christopher Rodrigues, Juan Gomez-Luna, Wen-mei Hwu

View

Tags: Code generation, Computer science, CUDA, Design space exploration, Heterogeneous systems, nVidia, performance portability, Tesla C2050, Tesla K20

November 25, 2016 by hgpu

Many-Core Architectures: Hardware-Software Optimization and Modeling Techniques

Christian Pinto

View

Tags: Computer science, CUDA, Design space exploration, nVidia, nVidia GeForce GTX 480, Thesis, Virtualization

July 17, 2015 by hgpu

MNN: a lightweight deep neural network inference engine

An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices

SolidTextureNets

On Demand Solid Texture Synthesis Using Deep 3D Networks

md_poly: A Performance-Portable Polyhedral Compiler Based on Multi-Dimensional Homomorphisms

md_poly: A Performance-Portable Polyhedral Compiler Based on Multi-Dimensional Homomorphisms

deepnetts: Deep Netts Pure Java Deep Learning Engine

Towards High Performance Java-based Deep Learning Frameworks

PASTA: A Parallel Sparse Tensor Algorithm Benchmark Suite

A Parallel Sparse Tensor Benchmark Suite on CPUs and GPUs

TACO: The Tensor Algebra Compiler (taco) computes sparse tensor expressions on CPUs and GPUs

A Unified Iteration Space Transformation Framework for Sparse and Dense Tensor Algebra

OpenCL-FPGA-LLVM: LLVM-based automation of memory decoupling for OpenCL applications on FPGAs

LLVM-based automation of memory decoupling for OpenCL applications on FPGAs

CUDAnative.jl: Julia support for native CUDA programming

Abstractions for Programming Graphics Processors in High-Level Programming Languages

GPU explicit-state model checking

Porting tree-based hash table compression to GPGPU model checking

OCLADock: OpenCL Accelerated Molecular Docking

Accelerating Molecular Docking by Parallelized Heterogeneous Computing – A Case Study of Performance, Quality of Results, and Energy-Efficiency using CPUs, GPUs, and FPGAs

See all packages

* * *

* * *

* * *

2020

April

27-29

Munich, Germany

8th International Workshop on OpenCL, including SYCLCon, 2019

2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

14

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

+

HGPU group © 2010-2020 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: