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High Performance Computing On Laptops With Multicores & GPUs. Sushil K. Prasad Computer Science sprasad@gsu.edu. About me. Research Area: Parallel and Distributed Algorithms and Systems - over multicores , GPUs, clusters, sensors, handhelds, web services, … - PowerPoint PPT Presentation
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High Performance Computing On Laptops With Multicores & GPUs
Sushil K. PrasadComputer Sciencesprasad@gsu.edu
About meResearch Area: Parallel and Distributed
Algorithms and Systems- over multicores, GPUs, clusters, sensors, handhelds, web services, …
Lab: Distributed and Mobile Systems (DiMoS)
at Ga. Tech campus, 5 PhD students, 2 M.S. students
IEEE TCPP Chair (elected) 2 NSF grants – currently looking for
PhD/MS/undergraduate students Distributed Algorithms High Performance Cloud Computing
Multicore & GPU Chips Inside a Laptop - 100s of processors
GPUs Vs Multicores
• Combined power exceeds 180 GFLOPs
Difficult to parallelize
Memory hierarchy is a barrier:
1 cycle core 3 cycles L1
cache 14 cycles L2 250 cycles
RAM
Intel Core-2 Duo Multicore
GPU: Graphics Processing Unit
Nvidia 280 GTX• 240 cores• Extreme memory hierarchy• Registers• Local memory• Shared memory/8
cores• Off chip Global
Memory• bottleneck bus to CPU
• Nvidia 8800 GTX
• Smith Waterman Seq Alignment, Fasta, and Blast
• Database: SwissProt
• Manavski and Valle 2008
Parallel Data Structures -Priority Queues
5 3 1 2
6 8 7 6 5 8 9 7
19 21
12 1423 34 25 3816 13 14 6510 12 15 9
• Large Scale Event Simulation• Immune System Simulation • VLSI Logic simulation
• Branch and Bound• Task Scheduling• Challenge: Fine Grained
Systems • Students: Dinesh Agarwal, Nick Mancuso
Parallel Priority Queues on Multicore
Effect of Prefetching on PPQs
00.020.040.060.080.1
0.120.140.160.180.2
1 2 3 4 5 6 7 8
# of processors
Tim
e ta
ken
(se
con
ds)
With PF Without PF
Legacy-Code to GPUs(Student: Chad Christopher)
Distributed Algorithms for Lifetime of Wireless Sensor Networks (Student: Akshaye Dhawan)
NP-Hard Distributed Problems in Networks
NSF Grant Minimum Vertex/Target Cover Minimum Triangle Packing Optimum mobile sensor network target
tracking Minimum channel assignment in mobile
ad-hoc networks Students: John Daigle, Thamer Sulaiman
April 19, 2023UM-Morris
13
Middleware for Mobile Ad–hoc Applications
Process Requests
Listener
1. Register
2. Lookup
3. p2p communication
Directory
Process Requests
Listener
Process Requests
Listener
Process Requests
Listener
Applications
Applications
Applications
Groupware
Deviceware
Deviceware
Deviceware
Mobile Support Station
BondFlow: Distributed Workflow over Web Services
(Student: Janaka Balasooriya)
Web service interface module
Proxy object generator module
Workflow configuration module
Execution module.
Mobile Web Services
Web Service Interface Module
WSDL Parser
WS Locator
Proxy Object Generator
Module
Workflow Configuration
Module
Web Services Registry (UDDI)
SOAP
Lookup for Web services
WSDL
Parsed WSDL
Workflow Execution Module
SOAP/ SyD
Web Bond Runtime
JVM
Current Belief
P2P Search based on Bayesian Decision and Value of Information (VOI) – (Student: Rasanjalee)
Peer Selection: Sending/forwarding query at
each node along query path = series of decision making steps based on incomplete data
A decision step: query the node that will reduce the uncertainty of current belief most.
Experimental Results:
A Priori Uncertainty : U1
A Posterior Uncertainty : U2
U1 –U2 = Information
The meaning of Uncertainty based Information
Decision step 1..
Decision step n
The reduction in uncertainty at each decision step
1 2 3 4 5
0102030405060708090
100
Success Ratio
SR-APS
SR-UCBPS
# walkers
Su
cces
s ra
tio
%
.
.
Middleware on Distributed Smart Cameras
cmucam3
Middleware on DSC networks provide a high-level programming
interface for applications. simplify the development of distributed
applications on DSC networks. provide networking functionality as part of
the middleware Student: Jayampathi Sampat
About meResearch Area: Parallel and Distributed
Algorithms and Systems- over multicores, GPUs, clusters, sensors, handhelds, web services, …
Lab: Distributed and Mobile Systems (DiMoS)
at Ga. Tech campus, 5 PhD students, 2 M.S. students
IEEE TCPP Chair (elected) 2 NSF grants – currently looking for
PhD/MS/undergraduate students Distributed Algorithms High Performance Cloud Computing
High Performance Computing On Laptops With Multicores & GPUs
Sushil K. PrasadComputer Sciencesprasad@gsu.edu
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