Mais conteúdo relacionado Semelhante a IAP09 CUDA@MIT 6.963 - Lecture 01: Logistics (Nicolas Pinto, MIT) (20) IAP09 CUDA@MIT 6.963 - Lecture 01: Logistics (Nicolas Pinto, MIT)1. 6.963
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Supercomputing on your desktop:
Programming the next generation of cheap
and massively parallel hardware using CUDA
Lecture 01
Nicolas Pinto (MIT)
Kick - Off session
12. Course Goals
• Learn how to program massively parallel
processors and achieve
–high performance
–functionality and maintainability
–scalability across future generations
• Acquire technical knowledge required to
achieve the above goals
–principles and patterns of parallel programming
–processor architecture features and constraints
–programming API, tools and techniques
6.963
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© David Kirk/NVIDIA and Wen-mei W. Hwu, 2007
ad
ECE 498AL1, University of Illinois, Urbana-Champaign
17. Class logistics
Teaching Staff (MIT)
GPU Computing with
CUDA David Luebke (NVIDIA)
CUDA Demos
Marc Adams (NVIDIA)
High-Throughput
Scientific Computing
Hanspeter Pfister (Harvard)
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ing
ach
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Faculty: Prof. Steven G. Johnson
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ach
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TAs: Justin Riley and Nicolas Poilvert
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St
ing
ach
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Instructor: Nicolas Pinto
Contact: pinto@mit.edu
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Lectures: M/W/F 10-12 (#32-155)
HandsOn: M/W/F 2-5 (#32-141)
Project Hours: T/R 2-5 (#3-370)
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S
/ CUDA Basics
/
/ CUDA Advanced
/
/ Theory
/
/ Case Studies
/
/ Projects
/
27. are
rdw
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19 MacBook Pro
28. are
rdw
Ha
$70,000+
from NVIDIA, Rowland/Harvard and MIT
(OEIT, DiCarlo Lab, Graphics CSAIL, EECS)
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Pr
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T Project Presentations
@the_end_of_the_course
MIT
6.963
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Pers ifts
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