English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Programs that make extensive use of widely shared var- iables are expected to achieve modest speedups for non-bus-based cache coherence protocols, particularly as the number of proces- sors sharing the data grows large. Protocols such as the IEEE Scalable Coherent Interface (SCI) are optimized for data that is not widely shared; the GLOW protocol extensions are specifically designed to address this limitation. The GLOW extensions take advantage of physical locality by mapping K-ary logical sharing trees to the network topology. This results in protocol messages that travel shorter distances, experiencing lower latency and con- suming less bandwidth. To build the sharing trees, GLOW caches directory information at strategic points in the network, allowing concurrency, and therefore, scalability, of read requests. Scalabil- ity in writes is achieved by exploiting the sharing tree to invalidate or update nodes in the sharing tree concurrently. We have defined the GLOW extensions with respect to SCI and we have implemented them in the Wisconsin Wind Tunnel (WWT) parallel discrete event simulator. We studied them on an example topology, the K-ary N- cube, and explored their scalability with four programs for large systems (up to 256 processors).

The GLOW cache coherence protocol extensions for widely shared data