메뉴 건너뛰기




Volumn , Issue , 2013, Pages

High throughput heavy hitter aggregation for modern SIMD processors

Author keywords

[No Author keywords available]

Indexed keywords

AGGREGATE FUNCTION; CACHE ACCESS; HIGH THROUGHPUT; PERFECT HASHING; SHARED NOTHING; SIMD INSTRUCTIONS; SIMD PROCESSORS; SMALL FOOTPRINTS;

EID: 84880524345     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2485278.2485284     Document Type: Conference Paper
Times cited : (29)

References (21)
  • 1
    • 33749585668 scopus 로고    scopus 로고
    • Monetdb/x100: Hyper-pipelining query execution
    • P. Boncz, M. Zukowski, and N. Nes. Monetdb/x100: Hyper-pipelining query execution. In CIDR, 2005.
    • (2005) CIDR
    • Boncz, P.1    Zukowski, M.2    Nes, N.3
  • 3
    • 85011093340 scopus 로고    scopus 로고
    • Adaptive aggregation on chip multiprocessors
    • J. Cieslewicz and K. A. Ross. Adaptive aggregation on chip multiprocessors. In VLDB, 2007.
    • (2007) VLDB
    • Cieslewicz, J.1    Ross, K.A.2
  • 4
    • 77954702544 scopus 로고    scopus 로고
    • Automatic contention detection and amelioration for data-intensive operations
    • J. Cieslewicz, K. A. Ross, K. Satsumi, and Y. Ye. Automatic contention detection and amelioration for data-intensive operations. In SIGMOD, 2010.
    • (2010) SIGMOD
    • Cieslewicz, J.1    Ross, K.A.2    Satsumi, K.3    Ye, Y.4
  • 5
    • 14844367057 scopus 로고    scopus 로고
    • An improved data stream summary: The count-min sketch and its applications
    • G. Cormode et al. An improved data stream summary: the count-min sketch and its applications. J. Algo., 55(1), 2005.
    • (2005) J. Algo , vol.55 , Issue.1
    • Cormode, G.1
  • 6
    • 84867128082 scopus 로고    scopus 로고
    • Finding frequent items in data streams
    • G. Cormode and M. Hadjieleftheriou. Finding frequent items in data streams. In VLDB, 2008.
    • (2008) VLDB
    • Cormode, G.1    Hadjieleftheriou, M.2
  • 7
    • 0002540034 scopus 로고    scopus 로고
    • A reliable randomized algorithm for the closest-pair problem
    • M. Dietzfelbinger et al. A reliable randomized algorithm for the closest-pair problem. J. Algorithms, 25(1), 1997.
    • (1997) J. Algorithms , vol.25 , Issue.1
    • Dietzfelbinger, M.1
  • 8
    • 84880526097 scopus 로고    scopus 로고
    • Weaknesses of cuckoo hashing with a simple universal hash class: The case of large universes
    • M. Dietzfelbinger and U. Schellbach. Weaknesses of cuckoo hashing with a simple universal hash class: The case of large universes. In SOFSEM, 2009.
    • (2009) SOFSEM
    • Dietzfelbinger, M.1    Schellbach, U.2
  • 9
    • 34547405655 scopus 로고    scopus 로고
    • Computing the distribution of the maximum in balls-and-boxes problems with application to clusters of disease cases
    • W. J. Ewens and H. S. Wilf. Computing the distribution of the maximum in balls-and-boxes problems with application to clusters of disease cases. PNAS, 104(27), 2007.
    • (2007) PNAS , vol.104 , Issue.27
    • Ewens, W.J.1    Wilf, H.S.2
  • 10
    • 0348252034 scopus 로고    scopus 로고
    • A simple algorithm for finding frequent elements in streams and bags
    • R. M. Karp et al. A simple algorithm for finding frequent elements in streams and bags. ACM T. Dat. S., 28(1), 2003.
    • (2003) ACM T. Dat. S , vol.28 , Issue.1
    • Karp, R.M.1
  • 11
    • 0034366238 scopus 로고    scopus 로고
    • Optimizing database architecture for the new bottleneck: Memory access
    • S. Manegold et al. Optimizing database architecture for the new bottleneck: memory access. VLDB J., 9(3), 2000.
    • (2000) VLDB J , vol.9 , Issue.3
    • Manegold, S.1
  • 12
    • 2442443820 scopus 로고    scopus 로고
    • Approximate frequency counts over data streams
    • G. S. Manku and R. Motwani. Approximate frequency counts over data streams. In VLDB, 2002.
    • (2002) VLDB
    • Manku, G.S.1    Motwani, R.2
  • 13
    • 33750185779 scopus 로고    scopus 로고
    • An integrated e• cient solution for computing frequent and top-k elements in data streams
    • A. Metwally D. Agrawal, and A. E. Abbadi. An integrated e• cient solution for computing frequent and top-k elements in data streams. ACM Trans. Database Syst, 31(3), 2006.
    • (2006) ACM Trans. Database Syst , vol.31 , Issue.3
    • Metwally, A.1    Agrawal, D.2    Abbadi, A.E.3
  • 14
    • 84880524790 scopus 로고
    • Finding repeating elements
    • Cornell University
    • J. Misra and D. Gries. Finding repeating elements. Technical report, Cornell University, 1982.
    • (1982) Technical Report
    • Misra, J.1    Gries, D.2
  • 15
    • 84863448825 scopus 로고    scopus 로고
    • E• ciently compiling e• cient query plans for modern hardware
    • T. Neumann. E• ciently compiling e• cient query plans for modern hardware. VLDB, 4(9), 2011.
    • (2011) VLDB , vol.4 , Issue.9
    • Neumann, T.1
  • 16
    • 2442420008 scopus 로고    scopus 로고
    • Cuckoo hashing
    • R. Pagh et al. Cuckoo hashing. J. Algorithms, 51(2), 2004.
    • (2004) J. Algorithms , vol.51 , Issue.2
    • Pagh, R.1
  • 17
    • 34548795866 scopus 로고    scopus 로고
    • E• cient hash probes on modern processors
    • K. A. Ross. E• cient hash probes on modern processors. In ICDE, 2007.
    • (2007) ICDE
    • Ross, K.A.1
  • 18
    • 84866027830 scopus 로고    scopus 로고
    • E• cient frequent item counting in multi-core hardware
    • P. Roy, J. Teubner, and G. Alonso. E• cient frequent item counting in multi-core hardware. In KDD, 2012.
    • (2012) KDD
    • Roy, P.1    Teubner, J.2    Alonso, G.3
  • 19
    • 79960192417 scopus 로고    scopus 로고
    • Scalable aggregation on multicore processors
    • Y. Ye, K. A. Ross, and N. Vesdapunt. Scalable aggregation on multicore processors. In DaMoN, 2011.
    • (2011) DaMoN
    • Ye, Y.1    Ross, K.A.2    Vesdapunt, N.3
  • 20
    • 0036360628 scopus 로고    scopus 로고
    • Implementing database operations using simd instructions
    • J. Zhou and K. A. Ross. Implementing database operations using simd instructions. In SIGMOD, 2002.
    • (2002) SIGMOD
    • Zhou, J.1    Ross, K.A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.