ASIC Clouds: Specializing the Datacenter for Planet-Scale Applications.
Planet-scale applications are driving the exponential growth of the Cloud, and datacenter specialization is the key enabler of this trend. GPU- and FPGA-based clouds have already been deployed to accelerate compute-intensive workloads. ASIC-based clouds are a natural evolution as cloud services expa...
| Publicado en: | Communications of the ACM Vol. 63; no. 7; pp. 103 - 110 |
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| Autores principales: | , , , , , |
| Formato: | Artículo |
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Association for Computing Machinery
Jul2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=144780584&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 144780584 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: Jul2020 vid: 63 iid: 7 pid: 68 pub: Association for Computing Machinery artinfo: ui: 144780584 10.1145/3399734 ppf: 103 ppct: 7 formats: tig: atl: ASIC Clouds: Specializing the Datacenter for Planet-Scale Applications. aug: au: Taylor, Michael Bedford Vega, Luis Khazraee, Moein Ikuo Magaki Davidson, Scott Richmond, Dustin affil: University of Washington, WA, USA UC San Diego, CA, USA su: Application-specific integrated circuits Cloud computing Central processing units Total cost of ownership Server farms (Computer network management) sug: subj: Application-specific integrated circuits Cloud computing Central processing units Total cost of ownership Server farms (Computer network management) ab: Planet-scale applications are driving the exponential growth of the Cloud, and datacenter specialization is the key enabler of this trend. GPU- and FPGA-based clouds have already been deployed to accelerate compute-intensive workloads. ASIC-based clouds are a natural evolution as cloud services expand across the planet. ASIC Clouds are purpose-built datacenters comprised of large arrays of ASIC accelerators that optimize the total cost of ownership (TCO) of large, high-volume scale-out computations. On the surface, ASIC Clouds may seem improbable due to high NREs and ASIC inflexibility, but large-scale ASIC Clouds have already been deployed for the Bitcoin cryptocurrency system. This paper distills lessons from these Bitcoin ASIC Clouds and applies them to other large scale workloads such as YouTube-style video-transcoding and Deep Learning, showing superior TCO versus CPU and GPU. It derives Pareto-optimal ASIC Cloud servers based on accelerator properties, by jointly optimizing ASIC architecture, DRAM, motherboard, power delivery, cooling, and operating voltage. Finally, the authors examine the impact of ASIC NRE and when it makes sense to build an ASIC Cloud. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2020 holdings: @attributes: islocal: N |
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