Accelerating Next-Generation Applications Via Secure and Reliable Compute-in-Memory Systems
通过安全可靠的内存计算系统加速下一代应用程序
基本信息
- 批准号:RGPIN-2021-03729
- 负责人:
- 金额:$ 2.48万
- 依托单位:
- 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
- 起止时间:2021-01-01 至 2022-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Computing systems execute important applications that form the backbone of the global economy, e.g., machine learning, data and graph analytics, transaction processing, and high-performance computing applications. Emerging next-generation applications include genome sequencing, precision medicine, virtual/augmented reality, autonomous vehicles, and smart homes/cities. These "Big Data" applications have fast-growing data requirements, leading to an ever-increasing memory footprint. Application performance is dependent on, and limited by, the memory system. Frequent data movements between processors and memory lead to slower execution and energy inefficiency. Slower execution could be the difference between online (real-time) and offline processing, making some applications impractical. Energy inefficiency leads to higher energy costs and a growing carbon footprint for computer systems. Compute in Memory (CIM) systems reduce data movement by performing computations closer to data, leading to significant speedups and energy savings. However, commercial adoption has been hindered by significant system challenges. My research program's long-term goal is to enable breakthrough improvements in performance, security, and energy efficiency for future memory systems. This benefits the Canadian economy by enabling real-time execution of key next-generation applications, and training highly qualified personnel for future careers in academia and industry. This proposal addresses two critical but mostly unexplored challenges for CIM systems: Security and reliability. CIM Security/Privacy. Memory is vulnerable to physical, covert and side-channel attacks that could leak programs' private data. To avoid leaks, memory data is encrypted, and is only decrypted when it enters the trusted execution domain (processors and caches). To maintain data integrity and prevent corruption, message authentication codes (MAC) are used. Since CIM computes on unencrypted data, decryption and checking integrity's overheads reduce or eliminate CIM benefits. CIM Reliability. Error rates in memory systems are increasing due to memory capacity scaling (higher number of more vulnerable bit cells), and malicious software that corrupts data. Errors can manifest as failures due to detectable but uncorrectable errors or undetectable errors. Memories deploy error-correcting codes (ECC) to protect against failures. Unfortunately, slow ECC (to offset higher error rates) reduces CIM performance and energy gains. Despite their importance for CIM's commercial adoption, little research has been done to address both challenges. This proposal targets novel software, systems and architecture mechanisms to fill this crucial gap with the following objectives: (1) Modeling security and reliability features for CIM systems; (2) Accelerating computations on encrypted data; (3) Exploring and mitigating side-channel attacks on CIM systems; (4) Accelerating reliable computations on unreliable data.
计算系统执行形成全球经济支柱的重要应用,例如机器学习、数据和图形分析、交易处理和高性能计算应用。新兴的下一代应用包括基因组测序、精确医学、虚拟/增强现实、自动驾驶汽车和智能家居/城市。这些大数据应用程序具有快速增长的数据需求,导致内存占用量不断增加。应用程序性能取决于存储系统,并受到存储系统的限制。处理器和内存之间频繁的数据移动会导致执行速度变慢和能源效率低下。执行速度较慢可能是在线(实时)和离线处理之间的区别,从而使一些应用程序不切实际。能源效率低下导致更高的能源成本和计算机系统不断增长的碳足迹。内存计算(CIM)系统通过执行更接近数据的计算来减少数据移动,从而显著加快速度并节省能源。然而,商业采用一直受到重大系统挑战的阻碍。我的研究计划的长期目标是为未来的存储系统在性能、安全性和能效方面实现突破性的改进。这使加拿大经济受益,因为它能够实时执行关键的下一代应用程序,并为未来的学术界和工业职业培训高素质的人员。这项建议解决了CIM系统面临的两个关键但大多未被探索的挑战:安全性和可靠性。CIM安全/隐私。内存容易受到物理、隐蔽和旁路攻击,这些攻击可能会泄露程序的私人数据。为了避免泄漏,内存数据被加密,并且只有在它进入可信执行域(处理器和缓存)时才被解密。为了维护数据完整性和防止损坏,使用消息验证码(MAC)。由于CIM对未加密的数据进行计算,因此解密和完整性检查的开销会减少或消除CIM的好处。CIM可靠性。由于内存容量扩展(更多更易受攻击的位单元)以及破坏数据的恶意软件,内存系统中的错误率正在增加。由于可检测但不可纠正的错误或不可检测的错误,错误可能表现为失败。存储器采用纠错码(ECC)来防止故障。不幸的是,较慢的ECC(以抵消较高的错误率)会降低CIM性能和能量收益。尽管它们对CIM的商业采用很重要,但针对这两个挑战的研究很少。该建议针对新的软件、系统和体系结构机制来填补这一关键空白,目标如下:(1)为CIM系统建模安全和可靠性特征;(2)加速加密数据的计算;(3)探索和减轻对CIM系统的侧信道攻击;(4)加速对不可靠数据的可靠计算。
项目成果
期刊论文数量(0)
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会议论文数量(0)
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Alameldeen, Alaa其他文献
CompressPoints: An Evaluation Methodology for Compressed Memory Systems
CompressPoints:压缩内存系统的评估方法
- DOI:
10.1109/lca.2018.2821163 - 发表时间:
2018 - 期刊:
- 影响因子:2.3
- 作者:
Choukse, Esha;Erez, Mattan;Alameldeen, Alaa - 通讯作者:
Alameldeen, Alaa
Alameldeen, Alaa的其他文献
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{{ truncateString('Alameldeen, Alaa', 18)}}的其他基金
Accelerating Next-Generation Applications Via Secure and Reliable Compute-in-Memory Systems
通过安全可靠的内存计算系统加速下一代应用程序
- 批准号:
RGPIN-2021-03729 - 财政年份:2022
- 资助金额:
$ 2.48万 - 项目类别:
Discovery Grants Program - Individual
Accelerating Next-Generation Applications Via Secure and Reliable Compute-in-Memory Systems
通过安全可靠的内存计算系统加速下一代应用程序
- 批准号:
DGECR-2021-00417 - 财政年份:2021
- 资助金额:
$ 2.48万 - 项目类别:
Discovery Launch Supplement
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