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SUMMARY:Efficient Analytical Query Processing on Multi-GPGPU Systems
DTSTART:20170626T140000
DTEND:20170626T160000
DTSTAMP:20260407T020903Z
UID:be0eb1b4f3660c6be6c3f71b4bb7a4b4666dfb3aa5871db9fa27ad78
CATEGORIES:Conferences - Seminars
DESCRIPTION:Periklis Chrysogelos\nEDIC candidacy exam\nExam president: Pro
 f. Robert West\nThesis advisor: Prof. Anastasia Ailamaki\nCo-examiner: Pro
 f. George Candea\n\nAbstract\nConventional wisdom suggests that handling t
 he explosion in terms of data volume only requires scaling out modern data
 base systems. Still\, besides scaling out\, database systems must consider
  how to fully exploit the abundant resources of modern servers\, such as m
 ultiple cores and large memories. In addition\, servers are becoming more 
 and more heterogeneous and the processing power is usually scattered acros
 s multiple processing nodes\, such as different CPU cores and sockets or e
 ven accelerators like GPGPUs. Analytical query processing has to overcome 
 the challenges introduced by heterogeneity and use the available resources
  as efficiently as possible to be able to keep up with the endless increas
 e of data volume.\n\nThis proposal discusses three existing works. The fir
 st two are aiming to efficiently process queries in a single-threaded setu
 p and extend such an engine into a parallel one\, respectively. The third 
 work profiles a GPU database to give a better insight on where time goes w
 hen GPU databases process analytical queries. Finally\, we conclude with o
 ur research proposal regarding analytical query processing in multi-GPU sy
 stems.\n\nBackground papers\nEfficiently compiling efficient query plans f
 or modern hardware\, by Neumann\, T. Proceedings of the VLDB Endowment 4\,
  9 (2011)\, 539-550.\nEncapsulation of parallelism in the volcano query pr
 ocessing system\, by Graefe\, G. In Proceedings of the 1990 ACM SIGMOD Int
 ernational Conference on Management of Data (New York\, NY\, USA\, 1990)\,
  SIGMOD ’90\, ACM\, pp. 102-111.\nThe yin and yang of processing data wa
 rehousing queries on gpu devices\, by Yuan\, Y.\, Lee\, R.\, and Zhang\, X
 .  Proceedings of the VLDB Endowment 6\, 10 (2013)\, 817-828.
LOCATION:BC 229 https://plan.epfl.ch/?room==BC%20229
STATUS:CONFIRMED
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