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Energy-efficient and High-bandwidth ...
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Moazeni, Sajjad.
Energy-efficient and High-bandwidth Density Monolithic Optical Transceivers in Advanced CMOS Processes.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Energy-efficient and High-bandwidth Density Monolithic Optical Transceivers in Advanced CMOS Processes./
作者:
Moazeni, Sajjad.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:
143 p.
附註:
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Contained By:
Dissertation Abstracts International80-01B(E).
標題:
Electrical engineering. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10845211
ISBN:
9780438325685
Energy-efficient and High-bandwidth Density Monolithic Optical Transceivers in Advanced CMOS Processes.
Moazeni, Sajjad.
Energy-efficient and High-bandwidth Density Monolithic Optical Transceivers in Advanced CMOS Processes.
- Ann Arbor : ProQuest Dissertations & Theses, 2018 - 143 p.
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Thesis (Ph.D.)--University of California, Berkeley, 2018.
Today's conventional cloud computing and mobile platforms have been challenged by the advent of Machine Learning (ML) and Internet of Things (IoT). The performance and diversity requirements of these applications demand the shift towards hyper-scale data centers, Exascale high-performance computing (HPC), energy-efficient edge computing, and new sensing and imaging modalities. My research goal is to design and implement large-scale and energy-efficient integrated systems that answer these technological changes by merging state-of-the-art electronics with photonics.
ISBN: 9780438325685Subjects--Topical Terms:
596380
Electrical engineering.
Energy-efficient and High-bandwidth Density Monolithic Optical Transceivers in Advanced CMOS Processes.
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Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
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Adviser: Vladimir Stojanovic.
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Thesis (Ph.D.)--University of California, Berkeley, 2018.
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Today's conventional cloud computing and mobile platforms have been challenged by the advent of Machine Learning (ML) and Internet of Things (IoT). The performance and diversity requirements of these applications demand the shift towards hyper-scale data centers, Exascale high-performance computing (HPC), energy-efficient edge computing, and new sensing and imaging modalities. My research goal is to design and implement large-scale and energy-efficient integrated systems that answer these technological changes by merging state-of-the-art electronics with photonics.
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This thesis developes several monolithic photonics platforms in advanced CMOS technologies that were designed as key enablers for the next-generation of integrated systems: (1) Using unmodified CMOS in 32/45nm SOI nodes places photonics next to one of the fastest transistors and enhances integrated system applications beyond the Moore-scaling, while being able to offload major communication tasks from more deeply-scaled compute and memory chips without the complications of 3D integration approaches. (2) Poly-silicon based photonics in bulk CMOS as a path for embedding photonics in the most advanced CMOS nodes (sub-10nm). We demonstrate system results using these platforms for the immediate application area of high-performance optical transceivers. We elaborate on the electronic-photonic co-optimization opportunities on the example of optical interconnect application, a 40Gb/s optical transmitter achieving the world record energy and bandwidth density. Furthermore, we explain how deep insight into details of an advanced CMOS process can leverage photonic device design, enabling new degrees of freedom in a seemingly constrained environment. Lastly, we demonstrate the first monolithic integrated photonics platform in a commercial 300mm-wafer bulk CMOS technology. We implemented the photonic system-on-chip (SoC) in this platform for in-situ device characterization and process development, and demonstrated wavelength division multiplexed (WDM) optical transceivers. These integrated platforms and system design methodologies can unlock new functionalities in many applications such as HPC, high-bandwidth wireless connectivity, LiDAR, bio-sensing, etc.
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