rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: GCA
    sub title: global congestion awareness for load balance in Networks-on-Chip
  name:
    name part: Ramakrishna, Mukund.
    role:
      role term: creator
  name:
    name part: Sprintson, Alexander
    role:
      role term: thesis advisor.
  name:
    name part: Gratz, Paul V.
    role:
      role term: thesis advisor.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: As modern CMPs scale to ever increasing core counts, Networks-on-Chip (NoCs) are emerging as an interconnection fabric, enabling communication between components. While NoCs are easy to implement and provide high and scalable bandwidth, current routing algorithms, such as dimension-ordered routing, suffer from poor load balance, leading to reduced throughput and high latencies. Improving load balance, hence, is critical in future CMP designs where increased latency leads to wasted power and energy waiting for outstanding requests to resolve. Adaptive routing is a known technique to improve load balance; however, prior adaptive routing techniques either use local, myopic information or misinformed, regionally-aggregated information to form their routing decisions. This thesis proposes a new, light-weight, adaptive routing algorithm for on-chip routers based on global link state and congestion information, Global Congestion Awareness (GCA). GCA leverages unused bits in existing packet header flits to "piggyback" congestion state information around the network and uses a simple, low-complexity route calculation unit, to calculate optimal packet paths to their destination without the myopia of local decisions, nor the aggregation of unrelated status information, found in prior designs. In particular GCA outperforms local adaptive routing by up to 82%, Regional Congestion Awareness (RCA) by up to 51%, and a recent competing adaptive routing algorithm, DAR, by 8% on average on realistic workloads.
  note: by Mukund Ramakrishna.
  note: "Major Subject: Computer Engineering"
  note: Electronic resource.
  note: Master of Science Texas A&M University 2012 http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11712
  note: Includes bibliographical references.
  note: Text (Thesis)
  subject:
    topic: Major Computer Engineering
  subject:
    topic: Computer architecture
  subject:
    topic: Multicores
  subject:
    topic: On-chip networks
  subject:
    topic: Networks-on-Chip
  subject:
    topic: Adaptive routing
  identifier: http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11712
  record info:
    record content source: TXA
    record creation date: 121119
    record change date: 20150922144243.0
    record identifier: in00002780520