tailieunhanh - báo cáo hóa học:" Research Article Hardware-Enabled Dynamic Resource Allocation for Manycore Systems Using Bidding-Based System Feedback"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Hardware-Enabled Dynamic Resource Allocation for Manycore Systems Using Bidding-Based System Feedback | Hindawi Publishing Corporation EURASIP Journal on Embedded Systems Volume 2010 Article ID 261434 21 pages doi 2010 261434 Research Article Hardware-Enabled Dynamic Resource Allocation for Manycore Systems Using Bidding-Based System Feedback Theocharis Theocharides 1 Maria K. Michael 1 Marios Polycarpou 1 and Ajit Dingankar2 1 Department of Electrical and Computer Engineering KIOS Research Center for Intelligent Systems and Networks University of Cyprus 1678 Nicosia Cyprus 2 Client Components Group Intel Corporation Folsom CA USA Correspondence should be addressed to Theocharis Theocharides ttheocharides@ Received 28 May 2010 Revised 6 October 2010 Accepted 13 October 2010 Academic Editor Shuvra Bhattacharyya Copyright 2010 Theocharis Theocharides et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Manycore architectures are expected to dominate future general-purpose and application-specific computing systems. The everincreasing number of on-chip processor cores and the associated interconnect complexities present significant challenges in the design optimization and operation of these systems. In this paper we investigate the applicability of intelligent dynamic system-level optimization techniques in addressing some manycore design challenges such as dynamic resource allocation. In particular we introduce hardware enabled system-level bidding-based algorithms as an efficient and real-time on-chip mechanism for resource allocation in homogeneous and heterogeneous MPSoC manycore architectures. We have also developed a low-level simulation framework to evaluate the proposed bidding-based algorithms in several on-chip network-connected manycore configurations. Experimental results indicate performance improvements between 8 -44 when compared to a standard on-chip static allocation while