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Intel Accelerators Ecosystem: An SoC-Oriented Perspective : Industry Product

Yifan Yuan, Ren Wang, Narayan Ranganathan, Nikhil Rao, Sanjay Kumar, Philip Lantz, Vivekananthan Sanjeepan, Jorge Cabrera‐Gámez, Atul Kwatra, Rajesh Sankaran, Ipoom Jeong, Nam Sung Kim

202417 citationsDOI

Abstract

A growing demand for hyperscale services has compelled hyperscalers to deploy more compute resources at an unprecedented pace, further accelerated by the demise of Dennard scaling. Meanwhile, a considerable portion of the compute resources are consumed to execute common functions present across the hyperscale services, i.e., datacenter taxes. These challenges motivated many to explore specialized accelerators for these functions. Leading such a technology trend, Intel has integrated diverse on-chip accelerators into its recent flagship datacenter CPU products. Furthermore, to support the easy and efficient use of these accelerators for successful deployment in production hyperscale services, Intel has developed a hardware/software ecosystem. In this paper, we first focus on Intel’s holistic efforts to build the hardware/software ecosystem, presenting key SoC-level features that facilitate efficient CPU-accelerator interaction, effortless programming and use, and scalable accelerator sharing and virtualization. Next, we delve into the functions, microarchitectures, and software stacks of three new on-chip accelerators: Data Streaming Accelerator (DSA), In-memory Analytics Accelerator (IAA), and Dynamic Load Balancer (DLB). Lastly, we demonstrate that Intel’s on-chip accelerators can not only significantly reduce the datacenter taxes but also accelerate data-intensive applications essential for hyperscale services, with little effort to use the accelerators.

Topics & Concepts

Perspective (graphical)EcosystemComputer scienceProduct (mathematics)Embedded systemOperating systemComputer architectureEcologyArtificial intelligenceBiologyMathematicsGeometryEmbedded Systems Design TechniquesParallel Computing and Optimization TechniquesInterconnection Networks and Systems