國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

A Statistical View of Architecture D...

Deng, Zhaoxia.

A Statistical View of Architecture Design.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A Statistical View of Architecture Design.
作者:	Deng, Zhaoxia.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, 2017
面頁冊數:	145 p.
附註:	Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
附註:	Adviser: Frederic T. Chong.
Contained By:	Dissertation Abstracts International79-08B(E).
標題:	Computer science.
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10636241
ISBN:	9780355733969

A Statistical View of Architecture Design.
Deng, Zhaoxia.

A Statistical View of Architecture Design. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 145 p.

Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.

Thesis (Ph.D.)--University of California, Santa Barbara, 2017.

Computer architectures are becoming more and more complicated to meet the continuously increasing demand on performance, security and sustainability from applications. Many factors exist in the design and engineering space of various components and policies in the architectures, and it is not intuitive how these factors interact with each other and how they make impacts on the architecture behaviors. Seeking for the best architectures for specific applications and requirements automatically is even more challenging. Meanwhile, the architecture design need to deal with more and more non-determinism from lower level technologies. Emerging technologies exhibit statistical properties inherently, such as the wearout phenomenon in NEMs, PCM, ReRAM, etc. Due to the manufacturing and processing variations, there also exists variability among different devices or within the same device (e.g. different cells on the same memory chip). Hence, to better understand and control the architecture behaviors, we introduce the statistical perspective of architecture design: by specifying the architectural design goals and the desired statistical properties, we guide the architecture design with these statistical properties and exploit a series of techniques to achieve these properties.

ISBN: 9780355733969Subjects--Topical Terms:

199325
Computer science.

A Statistical View of Architecture Design.
LDR:04722nmm a2200325 4500 001 523953
005 20180517120325.5
008 180709s2017 ||||||||||||||||| ||eng d
020 $a 9780355733969
035 $a (MiAaPQ)AAI10636241
035 $a (MiAaPQ)ucsb:13664
035 $a AAI10636241
040 $a MiAaPQ $c MiAaPQ
100 1 $a Deng, Zhaoxia. $3 795456
245 1 2 $a A Statistical View of Architecture Design.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 145 p.
500 $a Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
500 $a Adviser: Frederic T. Chong.
502 $a Thesis (Ph.D.)--University of California, Santa Barbara, 2017.
520 $a Computer architectures are becoming more and more complicated to meet the continuously increasing demand on performance, security and sustainability from applications. Many factors exist in the design and engineering space of various components and policies in the architectures, and it is not intuitive how these factors interact with each other and how they make impacts on the architecture behaviors. Seeking for the best architectures for specific applications and requirements automatically is even more challenging. Meanwhile, the architecture design need to deal with more and more non-determinism from lower level technologies. Emerging technologies exhibit statistical properties inherently, such as the wearout phenomenon in NEMs, PCM, ReRAM, etc. Due to the manufacturing and processing variations, there also exists variability among different devices or within the same device (e.g. different cells on the same memory chip). Hence, to better understand and control the architecture behaviors, we introduce the statistical perspective of architecture design: by specifying the architectural design goals and the desired statistical properties, we guide the architecture design with these statistical properties and exploit a series of techniques to achieve these properties.
520 $a In the first part of the thesis, we introduce Herniated Hash Tables. Our architectural design goal is that the hash table implementation is highly scalable in both storage efficiency and performance, while the desired statistical property is to achieve as good storage efficiency and performance as with uniform distributions given non-uniform distributions across hash buckets. Herniated Hash Tables exploit multi-level phase change memory (PCM) to in-place expand storage for each hash bucket to accommodate asymmetrically chained entries. The organization, coupled with an addressing and prefetching scheme, also improves performance significantly by creating more memory parallelism.
520 $a In the second part of the thesis, we introduce Lemonade from Lemons, harnessing device wearout to create limited-use security architectures . The architectural design goal is to create hardware security architectures that resist attacks by statistically enforcing an upper bound on hardware uses, and consequently attacks. The desired statistical property is that the system-level minimum and maximum uses can be guaranteed with high probabilities despite of device-level variability. We introduce techniques for architecturally controlling these bounds and explore the cost in area, energy and latency of using these techniques to achieve systemlevel usage targets given device-level wearout distributions.
520 $a In the third part of the thesis, we demonstrate Memory Cocktail Therapy: A General, Learning-Based Framework to Optimize Dynamic Tradeoffs in NVMs. Limited write endurance and long latencies remain the primary challenges of building practical memory systems from NVMs. Researchers have proposed a variety of architectural techniques to achieve different tradeoffs between lifetime, performance and energy efficiency; however, no individual technique can satisfy requirements for all applications and different objectives. Our architectural design goal is that NVM systems can achieve optimal tradeoffs for specific applications and objectives, and the statistical goal is that the selected NVM configuration is nearly optimal. Memory Cocktail Therapy uses machine learning techniques to model the architecture behaviors in terms of all the configurable parameters based on a small number of sample configurations. Then, it selects the optimal configuration according to user-defined objectives which leads to the desired tradeoff between performance, lifetime and energy efficiency.
590 $a School code: 0035.
650 4 $a Computer science. $3 199325
690 $a 0984
710 2 $a University of California, Santa Barbara. $b Computer Science. $3 795457
773 0 $t Dissertation Abstracts International $g 79-08B(E).
790 $a 0035
791 $a Ph.D.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10636241