Multi-Core Processors: A New Way Forward and Challenges

被引:11
|
作者
Roy, Abinash [1 ]
Xu, Jingye [1 ]
Chowdhury, Masud H. [1 ]
机构
[1] Univ Illinois, Dept Elect & Comp Engn, Chicago, IL 60607 USA
关键词
Power Consumption; Interconnect challenges; Design Automation; Software Adaptability; Multi-core Processor;
D O I
10.1109/ICM.2008.5393510
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Continuous effort to achieve higher performance without driving up the power consumption and thermal effects has led the researchers to look for alternative architectures for microprocessors. Like the parallel processing which is extensively used in today's all microprocessors, multi-core architecture which combines several independent microprocessor cores in a single die has currently become very popular in most high performance intergraded circuits. Although multi-core processor offers excellent instruction execution speed with reduced power consumption, optimizing performance of individual processors and then incorporating them by interconnection on a single chip is a non-trivial task. This paper investigates the leading challenges associated with current high performance multi-core processor in terms of interfacing different cores, design automation and verification, software adaptability.
引用
收藏
页码:454 / 457
页数:4
相关论文
共 50 条
  • [41] The promised future of multi-core processors in avionics systems
    Sander O.
    Bapp F.
    Dieudonne L.
    Sandmann T.
    Becker J.
    [J]. CEAS Aeronautical Journal, 2017, 8 (01) : 143 - 155
  • [42] An Efficient Programming Skeleton for Clusters of Multi-Core Processors
    Mina Hosseini Rad
    Ahmad Patooghy
    Mahdi Fazeli
    [J]. International Journal of Parallel Programming, 2018, 46 : 1094 - 1109
  • [43] Big Prime Field FFT on Multi-core Processors
    Covanov, Svyatoslav
    Mohajerani, Davood
    Maza, Marc Moreno
    Wang, Linxiao
    [J]. PROCEEDINGS OF THE 2019 ACM INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND ALGEBRAIC COMPUTATION (ISSAC '19), 2019, : 106 - 113
  • [44] Efficient and portable Winograd convolutions for multi-core processors
    Dolz, Manuel F.
    Martinez, Hector
    Castello, Adrian
    Alonso-Jorda, Pedro
    Quintana-Orti, Enrique S.
    [J]. JOURNAL OF SUPERCOMPUTING, 2023, 79 (10): : 10589 - 10610
  • [45] Accelerating sequential programs on commodity multi-core processors
    Zhang, Yuanming
    Xiao, Gang
    Baba, Takanobu
    [J]. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2014, 74 (04) : 2257 - 2265
  • [46] Acceleration of Dijkstra's Algorithm on Multi-core Processors
    Prasad, Abhay
    Krishnamurthy, Sukruth Kumar
    Kim, Youngsoo
    [J]. 2018 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC), 2018, : 95 - 99
  • [47] Scalable Parallelization of Skyline Computation for Multi-core Processors
    Chester, Sean
    Sidlauskas, Darius
    Assent, Ira
    Bogh, Kenneth S.
    [J]. 2015 IEEE 31ST INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 2015, : 1083 - 1094
  • [48] LightSaber: Efficient Window Aggregation on Multi-core Processors
    Theodorakis, Georgios
    Koliousis, Alexandros
    Pietzuch, Peter
    Pirk, Holger
    [J]. SIGMOD'20: PROCEEDINGS OF THE 2020 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2020, : 2505 - 2521
  • [49] Parallelization of an Evolutionary Algorithm on a Platform with Multi-core Processors
    Tsutsui, Shigeyoshi
    [J]. ARTIFICIAL EVOLUTION, 2010, 5975 : 61 - 73
  • [50] Performance optimisation of sequential programs on multi-core processors
    Tristram, Waide
    Bradshaw, Karen
    [J]. PROCEEDINGS OF THE SOUTH AFRICAN INSTITUTE FOR COMPUTER SCIENTISTS AND INFORMATION TECHNOLOGISTS CONFERENCE, 2012, : 119 - 128