TY - GEN
T1 - Speeding up scoring module of mass spectrometry based protein identification by GPU
AU - Li, You
AU - CHU, Xiaowen
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - Database searching is a main method for protein identification in shotgun proteomics, and many research efforts are dedicated to improving its effectiveness. However, the efficiency of database searching is facing a serious challenge, due to the ever fast growth of protein and peptide databases resulted from genome translations, enzymatic digestions, and post-translational modifications (PTMs). On the other hand, as a general-purpose and high performance parallel hardware, Graphics Processing Units (GPUs) develop continuously and provide another promising platform for parallelizing database searching based protein identification. It becomes very important to study how to speed up database search engines by GPUs for protein identification. In this paper, we mainly utilize GPUs to accelerate the scoring module, which is the most time-consuming component. Specifically, we study two popular scoring method: spectral dot product based method, which is used by X!Tandem, and kernel spectral dot product, which is used by pFind.
AB - Database searching is a main method for protein identification in shotgun proteomics, and many research efforts are dedicated to improving its effectiveness. However, the efficiency of database searching is facing a serious challenge, due to the ever fast growth of protein and peptide databases resulted from genome translations, enzymatic digestions, and post-translational modifications (PTMs). On the other hand, as a general-purpose and high performance parallel hardware, Graphics Processing Units (GPUs) develop continuously and provide another promising platform for parallelizing database searching based protein identification. It becomes very important to study how to speed up database search engines by GPUs for protein identification. In this paper, we mainly utilize GPUs to accelerate the scoring module, which is the most time-consuming component. Specifically, we study two popular scoring method: spectral dot product based method, which is used by X!Tandem, and kernel spectral dot product, which is used by pFind.
KW - GPU computing
KW - protein identification
KW - spectral dot product
UR - http://www.scopus.com/inward/record.url?scp=84870439008&partnerID=8YFLogxK
U2 - 10.1109/HPCC.2012.194
DO - 10.1109/HPCC.2012.194
M3 - Conference contribution
AN - SCOPUS:84870439008
SN - 9780769547497
T3 - Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012
SP - 1315
EP - 1320
BT - Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012
T2 - 14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012
Y2 - 25 June 2012 through 27 June 2012
ER -