Accelerators are becoming key elements of computing platforms for both data centers and mobile devices as they deliver energyefficient high performance for key computational kernels. However, the design and integration of such components is complex, especially for Big Data applications where they have very large workloads to elaborate. Properly customizing the accelerators' private local memories (PLMs) is of critical importance. To analyze this problem we design an accelerator for Collaborative Filtering by applying a system-level design methodology that allows us to synthesize many alternative micro-Architectures as we vary the PLM sizes. We then evaluate the resulting accelerators in terms of resource requirements for both embedded architectures and data centers as we vary the size and density of the workloads.

On the design of scalable and reusable accelerators for big data applications

Pilato, Christian;
2016-01-01

Abstract

Accelerators are becoming key elements of computing platforms for both data centers and mobile devices as they deliver energyefficient high performance for key computational kernels. However, the design and integration of such components is complex, especially for Big Data applications where they have very large workloads to elaborate. Properly customizing the accelerators' private local memories (PLMs) is of critical importance. To analyze this problem we design an accelerator for Collaborative Filtering by applying a system-level design methodology that allows us to synthesize many alternative micro-Architectures as we vary the PLM sizes. We then evaluate the resulting accelerators in terms of resource requirements for both embedded architectures and data centers as we vary the size and density of the workloads.
2016
2016 ACM International Conference on Computing Frontiers - Proceedings
9781450341288
Software
File in questo prodotto:
File Dimensione Formato  
pilato_BigDAW16.pdf

accesso aperto

: Post-Print (DRAFT o Author’s Accepted Manuscript-AAM)
Dimensione 572.59 kB
Formato Adobe PDF
572.59 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1069658
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 4
social impact