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Paving the Path for Heterogeneous Me...
~
Agarwal, Neha.
Paving the Path for Heterogeneous Memory Adoption in Production Systems.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Paving the Path for Heterogeneous Memory Adoption in Production Systems./
作者:
Agarwal, Neha.
面頁冊數:
1 online resource (148 pages)
附註:
Source: Dissertation Abstracts International, Volume: 78-11(E), Section: B.
Contained By:
Dissertation Abstracts International78-11B(E).
標題:
Computer engineering. -
電子資源:
click for full text (PQDT)
ISBN:
9781369901979
Paving the Path for Heterogeneous Memory Adoption in Production Systems.
Agarwal, Neha.
Paving the Path for Heterogeneous Memory Adoption in Production Systems.
- 1 online resource (148 pages)
Source: Dissertation Abstracts International, Volume: 78-11(E), Section: B.
Thesis (Ph.D.)
Includes bibliographical references
Systems from smartphones to data-centers to supercomputers are increasingly heterogeneous, comprising various memory technologies and core types. Heterogeneous memory systems provide an opportunity to suitably match varying memory access patterns in applications, reducing CPU time thus increasing performance per dollar resulting in aggregate savings of millions of dollars in large-scale systems. However, with increased provisioning of main memory capacity per machine and differences in memory characteristics (for example, bandwidth, latency, cost, and density), memory management in such heterogeneous memory systems poses multi-fold challenges on system programmability and design.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9781369901979Subjects--Topical Terms:
569006
Computer engineering.
Index Terms--Genre/Form:
554714
Electronic books.
Paving the Path for Heterogeneous Memory Adoption in Production Systems.
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Paving the Path for Heterogeneous Memory Adoption in Production Systems.
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Adviser: Thomas F Wenisch.
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Systems from smartphones to data-centers to supercomputers are increasingly heterogeneous, comprising various memory technologies and core types. Heterogeneous memory systems provide an opportunity to suitably match varying memory access patterns in applications, reducing CPU time thus increasing performance per dollar resulting in aggregate savings of millions of dollars in large-scale systems. However, with increased provisioning of main memory capacity per machine and differences in memory characteristics (for example, bandwidth, latency, cost, and density), memory management in such heterogeneous memory systems poses multi-fold challenges on system programmability and design.
520
$a
In this thesis, we tackle memory management of two heterogeneous memory systems: (a) CPU-GPU systems with a unified virtual address space, and (b) Cloud computing platforms that can deploy cheaper but slower memory technologies alongside DRAMs to reduce cost of memory in data-centers. First, we show that operating systems do not have sufficient information to optimally manage pages in bandwidth-asymmetric systems and thus fail to maximize bandwidth to massively-threaded GPU applications sacrificing GPU throughput. We present BW-AWARE placement/migration policies to support OS to make optimal data management decisions. Second, we present a CPU-GPU cache coherence design where CPU and GPU need not implement same cache coherence protocol but provide cache-coherent memory interface to the programmer. Our proposal is first practical approach to provide a unified, coherent CPU--GPU address space without requiring hardware cache coherence, with a potential to enable an explosion in algorithms that leverage tightly coupled CPU--GPU coordination.
520
$a
Finally, to reduce the cost of memory in cloud platforms where the trend has been to map datasets in memory, we make a case for a two-tiered memory system where cheaper (per bit) memories, such as Intel/Microns 3D XPoint, will be deployed alongside DRAM. We present Thermostat, an application-transparent huge-page-aware software mechanism to place pages in a dual-technology hybrid memory system while achieving both the cost advantages of two-tiered memory and performance advantages of transparent huge pages. With Thermostat's capability to control the application slowdown on a per application basis, cloud providers can realize cost savings from upcoming cheaper memory technologies by shifting infrequently accessed cold data to slow memory, while satisfying throughput demand of the customers.
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2018
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click for full text (PQDT)
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