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

With the continuously increasing integration level, manycore processorsystems are likely to be the coming system structure not only in HPC but alsofor desktop or mobile systems. Nowadays manycore processors like Tilera TILE,KALRAY MPPA or Intel SCC combine a rising number of cores in a tiledarchitecture and are mainly designed for high performance applications withfocus on direct inter-core communication. The current architectures havelimitations by central or sparse components like memory controllers, memory I/Oor inflexible memory management.  In the future highly dynamic workloads with multiple concurrently runningapplications, changing I/O characteristics and a not predictable memory usagehave to be utilized on these manycore systems. Consequently the memorymanagement has to become more flexible and distributed in nature and adaptivemechanisms and system structures are needed. With Self-aware Memory (SaM), adecentralized, scalable and autonomous self-optimizing memory architecture isdeveloped. This adaptive memory management can achieve higher flexibility andan easy usage of memory.  In this paper the concept of an ongoing decentralized self-optimization isintroduced and the evaluation of its various parameters is presented. Theresults show that the overhead of the decentralized optimization process isamortized by the optimized runtime using the appropriate parameter settings.

Evaluating the Self-Optimization Process of the Adaptive Memory Management Architecture Self-aware Memory