Introduction Computer Science Henri Bal Vrije Universiteit Amsterdam
COMMUNICATION COMMUNICATE COMMUNITY Henri Bal A PUBLIC-PRIVATE RESEARCH COMMUNITY.
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Transcript of COMMUNICATION COMMUNICATE COMMUNITY Henri Bal A PUBLIC-PRIVATE RESEARCH COMMUNITY.
COMMUNICATION
COMMUNICATE
COMMUNITY
Henri Bal
A PUBLIC-PRIVATE RESEARCH COMMUNITY
Agenda
• General introduction to COMMIT/– (slides by Arnold Smeulders)
• Example collaboration NLeSC & COMMIT/: global climate modelling– NLeSC eSalsa project– COMMIT/ IV-e project
COMMIT/
The public-private research community for ICT-research of 60+ (non)profit & 20 science partners.
Our mission is to deliver world-class ICT-research to create opportunities with more & more partners.
DIMENSIONS
ICT-science use-inspired science
Synergy between projects
Dissemination tell the story outside science
Valorization towards use in industry
Internationalization NL is not alone in this field
SUCCESSESICT-science
Synergy
SWEET
Euro-Par 2014 Achievement award
SUCCESSESDissemination
Valorization
InternationalizationInfoSys and Figshare become partners, EU projects, EIT-ICT, …….
THE BIG FUTURE OF DATAWe have presented
60 demonstrators: ICT Science Application Alternative application
for four audiences:
The Big Future of DataBig Data are not always Big.
Often they are: private interactive uncertain unordered new media
In short they are
overwhelming data.
The Big Future of Data
Data-Science will surpass ICT-Science,
that is our future.
IV-e: e-Infrastructure Virtualization fore-Science Applications (P20)
• e-Infrastructures become very complicated– Distributed & heterogeneous
• P20 tries to simplify the e-Infrastructure, ease programming and integration
• WP5 studies how to effectively use GPUs for data processing (imaging) and computing
vrije Universiteit
Global Climate Modeling
COMMIT/
GPU Computing
• Offload expensive kernels for Parallel Ocean Program (POP) from CPU to GPU– Many kernels, fairly easy to port to
GPUs– Execution time becomes virtually 0
• New bottleneck: I/O between CPU & GPUCPU
hostmemory
GPU devicememory
Host
Device
PCI Express link
Different methods for CPU-GPU communication
• Memory copies (explicit)– No overlap with GPU computation
• Device-mapped host memory (implicit)– Allows fine-grained overlap between computation
and communication in either direction• CUDA Streams or OpenCL command-queues
– Allows overlap between computation and communication in different streams
• Any combination of the above
Problem
• ICT problem:– Which method will be most efficient for a given
GPU kernel? Implementing all can be a large effort• Solution:
– Create a performance model that identifies the best implementation:
• Which strategy for overlapping computation and communication is best for the given program?
Ben van Werkhoven, Jason Maassen, Frank Seinstra & Henri Bal: Performance models for CPU-GPU data transfers, CCGrid2014(nominated for best-paper-award, top 1%)
MOVIE
Example result
Measured Model
Discussion
• Good example of use-inspired Computer Science research
• Many other application domains that use accelerators face the same problem– Digital forensics, water management, astronomy …
• All details:
27 October 2014 1 October 2014
Different GPUs (state kernel)
Different GPUs (buoydiff)
Global Climate Modeling
• Understand future local sea level changes• Needs high-resolution simulations• Combine two approaches:
– Distributed computing (multiple resources)• Ibis couples models for land, ice, ocean, atmosphere
– GPUs(Graphics processing units)
COMMIT/
Comes with spreadsheet