13583
Ken Miura, Tetsuaki Mano, Atsushi Kanehira, Yuichiro Tsuchiya, Tatsuya Harada
MILJS is a collection of state-of-the-art, platform-independent, scalable, fast JavaScript libraries for matrix calculation and machine learning. Our core library offering a matrix calculation is called Sushi, which exhibits far better performance than any other leading machine learning libraries written in JavaScript. Especially, our matrix multiplication is 177 times faster than the fastest JavaScript benchmark. […]
Theo M. Nieuwenhuizen, Matthew T.P. Liska
Stochastic electrodynamics is a classical theory which assumes that the physical vacuum consists of classical stochastic fields with average energy $frac{1}{2}hbar omega$ in each mode, i.e., the zero-point Planck spectrum. While this classical theory explains many quantum phenomena related to harmonic oscillator problems, hard results on nonlinear systems are still lacking. In this work the […]
View View   Download Download (PDF)   
Dzmitry Razmyslovich, Guillermo Marcus, Markus Gipp, Marc Zapatka, Andreas Szillus
In this paper we present an implementation of the Smith-Waterman algorithm. The implementation is done in OpenCL and targets high-end GPUs. This implementation is capable of computing similarity indexes between reference and query sequences. The implementation is designed for the sequence alignment paths calculation. In addition, it is capable of handling very long reference sequences […]
Paul Harvey, Saji Hameed, Wim Vanderbauwhede
FLEXPART is a popular simulator that models the transport and diffusion of air pollutants, based on the Lagrangian approach. It is capable of regional and global simulation and supports both forward and backward runs. A complex model like this contains many calculations suitable for parallelisation. Recently, a GPU-accelerated version of the simulator (FLEXCPP) has been […]
View View   Download Download (PDF)   
Angelos Trigkas
OpenCL SYCL is a new heterogeneous and parallel programming framework created by the Khronos Group that tries to bring OpenCL programming into C++. In particular, it enables C++ developers to create OpenCL kernels, using all the popular C++ features, such as classes, inheritance and templates. What is more, it dramatically reduces programming effort and complexity, […]
View View   Download Download (PDF)   
Philippe Helluy, Thomas Strub, Michel Massaro, Malcolm Roberts
Hyperbolic conservation laws are important mathematical models for describing many phenomena in physics or engineering. The Finite Volume (FV) method and the Discontinuous Galerkin (DG) methods are two popular methods for solving conservation laws on computers. Those two methods are good candidates for parallel computing: a) they require a large amount of uniform and simple […]
View View   Download Download (PDF)   
Rashid Kaleem, Sreepathi Pai, Keshav Pingali
Irregular algorithms such as Stochastic Gradient Descent (SGD) can benefit from the massive parallelism available on GPUs. However, unlike in data-parallel algorithms, synchronization patterns in SGD are quite complex. Furthermore, scheduling for scale-free graphs is challenging. This work examines several synchronization strategies for SGD, ranging from simple locking to conflict-free scheduling. We observe that static […]
View View   Download Download (PDF)   
Ang Li, Hammad Mazhar, Radu Serban, Dan Negrut
ViennaCL is a free open-source linear algebra library for computations on many-core architectures (GPUs, MIC) and multi-core CPUs. The library is written in C++ and supports CUDA, OpenCL, and OpenMP. In addition to core functionality and many other features including BLAS level 1-3 support and iterative solvers, the latest release family ViennaCL 1.6.x provides fast […]
View View   Download Download (PDF)   
Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat
On modern parallel architectures, floating-point computations may become non-deterministic and, therefore, non-reproducible mainly due to non-associativity of floating-point operations. We propose an algorithm to solve dense triangular systems by leveraging the standard parallel triangular solver and our, recently introduced, multi-level exact summation approach. Finally, we present implementations of the proposed fast reproducible triangular solver and […]
Thomas Weber
The adaptive subdivision step for surface tessellation is a key component of the Reyes rendering pipeline. While this operation has been successfully parallelized for execution on the GPU using a breadth-first traversal, the resulting implementations are limited by their high worst-case memory consumption and high global memory bandwidth utilization. This report proposes an alternate strategy […]
Yash Ukidave, Fanny Nina Paravecino, Leiming Yu, Charu Kalra, Amir Momeni, Zhongliang Chen, Nick Materise, Brett Daley, Perhaad Mistry, David Kaeli
Heterogeneous systems consisting of multi-core CPUs, Graphics Processing Units (GPUs) and many-core accelerators have gained widespread use by application developers and data-center platform developers. Modern day heterogeneous systems have evolved to include advanced hardware and software features to support a spectrum of application patterns. Heterogeneous programming frameworks such as CUDA, OpenCL, and OpenACC have all […]
Craig Rasmussen, Matthew Sottile, Daniel Nagle, Soren Rasmussen
Emerging hybrid accelerator architectures for high performance computing are often suited for the use of a data-parallel programming model. Unfortunately, programmers of these architectures face a steep learning curve that frequently requires learning a new language (e.g., OpenCL). Furthermore, the distributed (and frequently multi-level) nature of the memory organization of clusters of these machines provides […]
View View   Download Download (PDF)   
Page 1 of 10912345...102030...Last »

* * *

* * *

Like us on Facebook

HGPU group

218 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1403 peoples are following HGPU @twitter

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2015 hgpu.org

All rights belong to the respective authors

Contact us: