Enhancing computation-to-core assignment with physical location information

Cited 9 time in webofscience Cited 1 time in scopus
  • Hit : 193
  • Download : 0
Going beyond a certain number of cores in modern architectures requires an on-chip network more scalable than conventional buses. However, employing an on-chip network in a manycore system (to improve scalability) makes the latencies of the data accesses issued by a core non-uniform. This non-uniformity can play a significant role in shaping the overall application performance. This work presents a novel compiler strategy which involves exposing architecture information to the compiler to enable an optimized computation-to-core mapping. Specifically, we propose a compiler-guided scheme that takes into account the relative positions of (and distances between) cores, last-level caches (LLCs) and memory controllers (MCs) in a manycore system, and generates a mapping of computations to cores with the goal of minimizing the on-chip network traffic. The experimental data collected using a set of 21 multi-threaded applications reveal that, on an average, our approach reduces the on-chip network latency in a 6×6 manycore system by 38.4% in the case of private LLCs, and 43.8% in the case of shared LLCs. These improvements translate to the corresponding execution time improvements of 10.9% and 12.7% for the private LLC and shared LLC based systems, respectively.
Publisher
Association for Computing Machinery
Issue Date
2018-06-18
Language
English
Citation

39th ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2018, pp.312 - 327

ISSN
0362-1340
DOI
10.1145/3192366.3192386
URI
http://hdl.handle.net/10203/269575
Appears in Collection
EE-Conference Papers(학술회의논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 9 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0