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

Integrated CPU-GPU architecture provides excellent acceleration capabilitiesfor data parallel applications on embedded platforms while meeting the size,weight and power (SWaP) requirements. However, sharing of main memory betweenCPU applications and GPU kernels can severely affect the execution of GPUkernels and diminish the performance gain provided by GPU. For example, in theNVIDIA Tegra K1 platform which has the integrated CPU-GPU architecture, wenoticed that in the worst case scenario, the GPU kernels can suffer as much as4X slowdown in the presence of co-running memory intensive CPU applicationscompared to their solo execution. In this paper, we propose a softwaremechanism, which we call BWLOCK++, to protect the performance of GPU kernelsfrom co-scheduled memory intensive CPU applications.

Protecting real-time GPU kernels on integrated CPU-GPU SoC platforms