Architectural Techniques to Sustain Moore's Law to Enable Reliable, Secure, and Efficient Memory Systems
Architectural Techniques to Sustain Moore's Law to Enable Reliable, Secure, and Efficient Memory Systems
批准号:
RGPIN-2019-05059
负责人:
Nair, PrashantJayaprakash
金额:
$2.04万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2021
资助国家:
加拿大
项目状态:
已结题
起止时间:
2021-01-01 至 2022-12-31
中文摘要
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英文摘要
Moore's law has been instrumental in enabling scalable high-capacity memory systems. Unfortunately, sustaining Moore's law is challenging, as scaling the feature sizes of memory cells also reduces their reliability and makes them insecure. The long-term mission of this research is to investigate clever schemes that enable reliable and secure memory systems for a wide range of applications across different computing systems. Our research will significantly enhance energy efficiency, reduce energy costs, and help build high-performance computing systems. This work will enable Canadians to develop computing systems that provide significant economic and environmental gains. On a technological front, enabling secure and reliable high-capacity memory systems is essential for building data centers, smartphones, desktops, and supercomputers. Furthermore, these systems are instrumental in enabling Canada to be a leader in cloud computing, machine learning and artificial intelligence, commerce, and scientific computing. To this end, this program aims to provide three main research themes. 1. Computer hardware and architecture for fault tolerance: To help sustain Moore's law by improving memory reliability by using architecture and system-wide strategies. Currently, memory systems distribute data across several memory dies and keep error-codes to correct faulty data. Our program will go beyond these approaches and investigate cross-layer schemes, data redundancy strategies, new memory technologies, cell variability, and page mapping schemes to improve reliability further. 2. Security and Privacy: In this era of big data, machine learning and artificial intelligence, memory systems are increasingly being used to store and provide sensitive data. As the reliability of memory systems reduces, it is becoming even more challenging to store data securely. To make matters worse, as current architecture and system-level solutions tend to have significant performance and power overheads. Our program will look at architecture and systems-level solutions that will enable high security at low-costs. 3. Data Management: As memory capacity increases, its bandwidth also needs to grow proportionally. This program will investigate data compression strategies to enhance bandwidth seamlessly. Data compression in current systems tends to require massive software support and also incurs additional hardware overheads. Our program will explore low-cost data compression strategies at architecture and system-level for main memory, caches, and storage. Development of highly qualified personnel (HQP) is a critical requirement for Canada. One of the critical goals of this program is to train HQP to develop vital skills in the areas of computer architecture, statistics and probability theory, mathematical analysis, performance analysis, operating systems, compilers, and programming languages.
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Architectural Techniques to Sustain Moore's Law to Enable Reliable, Secure, and Efficient Memory Systems
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批准号:RGPIN-2019-05059
-
项目类别:Discovery Grants Program - Individual
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资助金额:$2.04万
-
财政年份:2022
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负责人:Nair, PrashantJayaprakash
-
依托单位:
Architectural Techniques to Sustain Moore's Law to Enable Reliable, Secure, and Efficient Memory Systems
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批准号:RGPIN-2019-05059
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$2.04万
-
财政年份:2020
-
负责人:Nair, PrashantJayaprakash
-
依托单位:
Architectural Techniques to Sustain Moore's Law to Enable Reliable, Secure, and Efficient Memory Systems
-
批准号:RGPIN-2019-05059
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$2.04万
-
财政年份:2019
-
负责人:Nair, PrashantJayaprakash
-
依托单位:
Architectural Techniques to Sustain Moore's Law to Enable Reliable, Secure, and Efficient Memory Systems
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批准号:DGECR-2019-00322
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项目类别:Discovery Launch Supplement
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资助金额:$0.91万
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财政年份:2019
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负责人:Nair, PrashantJayaprakash
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依托单位:
国内基金
海外基金
EstimatingLarge Demand Systems with MachineLearning Techniques
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批准号:--
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项目类别:外国学者研究基金
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资助金额:--
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批准年份:2024
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负责人:IoshuaAlex
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依托单位: