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SUMMARY:GPU programming:  bugs\, pitfalls and the importance of correctnes
 s in biomedical and scientific applications - Professor Miriam Leeser\, No
 rtheastern University
DTSTART:20100719T090000Z
DTEND:20100719T100000Z
UID:TALK25405@talks.cam.ac.uk
CONTACT:Microsoft Research Cambridge Talks Admins
DESCRIPTION:*Abstract:* GPUs are being used to accelerate many biomedical 
 and scientific applications.  My research group is accelerating applicatio
 ns including: i) lung tumor tracking to better pinpoint the tumor in radia
 tion therapy and ii) in vivo imaging of tumors in live animals.  In these 
 and many other applications\, high confidence in the correctness of the re
 sult is essential.  At the same time\, a GPU program is by its nature mass
 ively parallel\,  launching hundreds or thousands of threads simultaneousl
 y.  Such programs are extremely difficult to debug.  Symbolic methods are 
 essential for reasoning about the concurrency inherent in these programs a
 nd their many different possible behaviors due to interleaving\, memory in
 terfacing and barrier synchronization.  In this talk\, I will discuss the 
 applications we are working on\, common coding errors in GPU programs\, an
 d why we believe that formal methods will help both finding bugs and givin
 g users an increased confidence of the correctness of their GPU programs. 
  We are also investigating arithmetic divergence between CPU and GPU code 
 and how to characterize the errors between the two.  \n\n*Biography:* Prof
 essor Miriam Leeser received the BS degree in Electrical Engineering from 
 Cornell University and the Diploma and PhD in Computer Science from Cambri
 dge University in England. In 1992\, she received a National Science Found
 ation CAREER award to conduct research into floating point arithmetic. She
  has been on the faculty of Northeastern since 1996\, where she is head of
  the Reconfigurable Computing Laboratory and a member of the computer engi
 neering research group and the Center for Communications and Digital Signa
 l Processing. She is conducting research into accelerating image and signa
 l processing applications with nontraditional computer architectures\, inc
 luding FPGAs\, GPUs\, and the Cell Broadband Engine. Her research includes
  building tools that enable application programmers to make use of highly 
 optimized implementations developed for these platforms.
LOCATION:Small Lecture Room\, Microsoft Research\, Roger Needham Building\
 , 7 J J Thomson Avenue\, Cambridge CB3 0FB
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