GTC ON-DEMAND

 
SEARCH SESSIONS
SEARCH SESSIONS

Search All
 
Refine Results:
 
Year(s)

SOCIAL MEDIA

EMAIL SUBSCRIPTION

 
 

GTC ON-DEMAND

Genomics & Bioinformatics
Presentation
Media
A Scalable Short-read Sequence Aligner Using a CUDA Kernel Pipeline
Abstract:

The Department of Physics and Astronomy at Johns Hopkins University is currently constructing a new computer cluster to facilitate high-throughput data-intensive computation on terabyte-scale data, including the analysis of genomic sequence data. Compute nodes in the cluster contain multiple CPU cores, 100GB or more of system RAM, and one or more GPUs; a prototype node is implemented with 12 CPU cores (24 hyperthreads), 144GB of RAM, and four NVIDIA C2070s. In this session we will describe the design of a genomic sequence-alignment application that targets the cluster compute-node hardware. We will discuss the algorithms we use and how they are implemented as CUDA kernels, point out the key optimizations in the implementation, and look at the performance of the software.

 
Topics:
Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2013
Session ID:
S3092
Streaming:
Download:
Share: