Lin Ma, Roger D. Chamberlain
Graphics engines are excellent execution platforms for high-throughput computations that exploit a large degree of available parallelism. The achieved performance is, however, highly dependent on the access patterns that the application imposes on the memory subsystem. Here, we propose an analytic model that helps improve the understanding of the performance of memory-limited kernels that employ […]
View View   Download Download (PDF)   
Shucai Xiao, Heshan Lin, Wu-chun Feng
The "Basic Local Alignment Search Tool” (BLAST) is arguably the most widely used computational tool in bioinformatics. However, the computational power required for routine BLAST analysis has been outstripping Moore’s Law due to the exponential growth in the size of the genomic sequence databases that BLAST searches on. To address the above issue, we propose […]
View View   Download Download (PDF)   
Gang Wei, Chao Ma, Songwen Pei, Baifeng Wu
Sequence alignment is one of the most fundamental and important operation in bioinformatics. Through sequence alignment, we can find the sequence’s information of function, structure and evolution. BLAST is one of the most popular algorithms in the field of sequence alignment. In this paper, we have designed a GPU-based parallel BLAST algorithm and implemented it […]
Huang Lican, Hu Ya
Sequence alignment is one of the most fundamental and important operation in Bioinformatics. Among lots of Sequence alignment tools, Blast is one of the most popular algorithms. In this paper, we describe the primary strategy of a GPU-based parallel computing on Blast program.
View View   Download Download (PDF)   
Weiguo Liu, Bertil Schmidt, Wolfgang Muller-Wittig
Scanning protein sequence database is an often repeated task in computational biology and bioinformatics. However, scanning large protein databases, such as GenBank, with popular tools such as BLASTP requires long runtimes on sequential architectures. Due to the continuing rapid growth of sequence databases, there is a high demand to accelerate this task. In this paper, […]
Adrianto Wirawan, Chee Keong K. Kwoh, Nim Tri T. Hieu, Bertil Schmidt
BACKGROUND: The exponential growth of available biological data has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing exponentially as well. The recent emergence of accelerator technologies has made it possible to achieve an excellent improvement in execution time for many […]
Panagiotis D. Vouzis, Nikolaos V. Sahinidis
MOTIVATION: The Basic Local Alignment Search Tool (BLAST) is one of the most widely used bioinformatics tools. The widespread impact of BLAST is reflected in over 53,000 citations that this software has received in the past two decades, and the use of the word "blast" as a verb referring to biological sequence comparison. Any improvement […]

* * *

* * *

Follow us on Twitter

HGPU group

1660 peoples are following HGPU @twitter

Like us on Facebook

HGPU group

334 people like HGPU on Facebook

* * *

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 12.3
  • SDK: AMD APP SDK 3.0

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: