We propose SoCurity, the first NoC counter-based hardware monitoring approach for enhancing heterogeneous SoC security. With SoCurity, we develop a fast, lightweight anomalous activity detection system leveraging semi-supervised machine learning models that require no prior attack knowledge for detecting anomalies. We demonstrate our techniques with a case study on a real SoC for a connected autonomous vehicle system and find up to 96% detection accuracy.
{"title":"SoCurity: A Design Approach for Enhancing SoC Security","authors":"Naorin Hossain;Alper Buyuktosunoglu;John-David Wellman;Pradip Bose;Margaret Martonosi","doi":"10.1109/LCA.2023.3301448","DOIUrl":"10.1109/LCA.2023.3301448","url":null,"abstract":"We propose SoCurity, the first NoC counter-based hardware monitoring approach for enhancing heterogeneous SoC security. With SoCurity, we develop a fast, lightweight anomalous activity detection system leveraging semi-supervised machine learning models that require no prior attack knowledge for detecting anomalies. We demonstrate our techniques with a case study on a real SoC for a connected autonomous vehicle system and find up to 96% detection accuracy.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"22 2","pages":"105-108"},"PeriodicalIF":2.3,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42292159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Processing-in-memory (PIM) is the most promising paradigm to address the bandwidth bottleneck in deep neural network (DNN) accelerators. However, the algorithmic and dataflow structure of DNNs still necessitates moving a large amount of data across banks inside the memory device to bring input data and their corresponding model parameters together, negatively shifting part of the bandwidth bottleneck to the in-memory data communication infrastructure. To alleviate this bottleneck, we present Smart Memory , a highly parallel in-memory DNN accelerator for 3D memories that benefits from a scalable high-bandwidth in-memory network. Whereas the existing PIM designs implement the compute units and network-on-chip on the logic die of the underlying 3D memory, in Smart Memory the computation and data transmission tasks are distributed across the memory banks. To this end, each memory bank is equipped with (1) a very simple processing unit to run neural networks, and (2) a circuit-switched router to interconnect memory banks by a 3D network-on-memory. Our evaluation shows 44% average performance improvement over state-of-the-art in-memory DNN accelerators.
{"title":"Smart Memory: Deep Learning Acceleration in 3D-Stacked Memories","authors":"Seyyed Hossein SeyyedAghaei Rezaei;Parham Zilouchian Moghaddam;Mehdi Modarressi","doi":"10.1109/LCA.2023.3287976","DOIUrl":"10.1109/LCA.2023.3287976","url":null,"abstract":"Processing-in-memory (PIM) is the most promising paradigm to address the bandwidth bottleneck in deep neural network (DNN) accelerators. However, the algorithmic and dataflow structure of DNNs still necessitates moving a large amount of data across banks inside the memory device to bring input data and their corresponding model parameters together, negatively shifting part of the bandwidth bottleneck to the in-memory data communication infrastructure. To alleviate this bottleneck, we present \u0000<italic>Smart Memory</i>\u0000, a highly parallel in-memory DNN accelerator for 3D memories that benefits from a scalable high-bandwidth in-memory network. Whereas the existing PIM designs implement the compute units and network-on-chip on the logic die of the underlying 3D memory, in \u0000<italic>Smart Memory</i>\u0000 the computation and data transmission tasks are distributed across the memory banks. To this end, each memory bank is equipped with (1) a very simple processing unit to run neural networks, and (2) a circuit-switched router to interconnect memory banks by a 3D network-on-memory. Our evaluation shows 44% average performance improvement over state-of-the-art in-memory DNN accelerators.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"23 1","pages":"137-141"},"PeriodicalIF":2.3,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135784868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-21DOI: 10.1109/LCA.2023.3297875
Gururaj Saileshwar;Moinuddin Qureshi
This letter studies common modeling pitfalls in security analyses of hardware defenses to highlight the importance of accurate reproduction of defenses. We provide a case study of MIRAGE (Saileshwar and Qureshi 2021), a defense against cache side channel attacks, and analyze its incorrect modeling in a recent work (Chakraborty et al., 2023) that claimed to break its security. We highlight several modeling pitfalls that can invalidate the security properties of any defense including a) incomplete modeling of components critical for security, b) usage of random number generators that are insufficiently random, and c) initialization of system to improbable states, leading to an incorrect conclusion of a vulnerability, and show how these modeling bugs incorrectly cause set conflicts to be observed in a recent work’s (Chakraborty et al., 2023) model of MIRAGE. We also provide an implementation addressing these bugs that does not incur set-conflicts, highlighting that MIRAGE is still unbroken.
本文研究了硬件防御安全分析中常见的建模缺陷，以强调准确复制防御的重要性。我们提供了MIRAGE的案例研究(Saileshwar和Qureshi 2021)，这是一种针对缓存侧通道攻击的防御，并在最近的一项工作(Chakraborty等人，2023)中分析了其错误的建模，该工作声称破坏了其安全性。我们强调了几个可以使任何防御的安全属性无效的建模缺陷，包括a)对安全至关重要的组件的不完整建模，b)使用随机数生成器的随机性不足，以及c)将系统初始化到不可能的状态，导致对漏洞的错误结论，并展示了这些建模错误如何在最近的工作(Chakraborty et al.， 2023) MIRAGE模型中观察到的集合冲突。我们还提供了一个解决这些错误的实现，它不会引起集合冲突，强调MIRAGE仍然是未被破坏的。
{"title":"The Mirage of Breaking MIRAGE: Analyzing the Modeling Pitfalls in Emerging “Attacks” on MIRAGE","authors":"Gururaj Saileshwar;Moinuddin Qureshi","doi":"10.1109/LCA.2023.3297875","DOIUrl":"10.1109/LCA.2023.3297875","url":null,"abstract":"This letter studies common modeling pitfalls in security analyses of hardware defenses to highlight the importance of accurate reproduction of defenses. We provide a case study of MIRAGE (Saileshwar and Qureshi 2021), a defense against cache side channel attacks, and analyze its incorrect modeling in a recent work (Chakraborty et al., 2023) that claimed to break its security. We highlight several modeling pitfalls that can invalidate the security properties of any defense including a) incomplete modeling of components critical for security, b) usage of random number generators that are insufficiently random, and c) initialization of system to improbable states, leading to an incorrect conclusion of a vulnerability, and show how these modeling bugs incorrectly cause set conflicts to be observed in a recent work’s (Chakraborty et al., 2023) model of MIRAGE. We also provide an implementation addressing these bugs that does not incur set-conflicts, highlighting that MIRAGE is still unbroken.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"22 2","pages":"121-124"},"PeriodicalIF":2.3,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48105760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-19DOI: 10.1109/LCA.2023.3296251
Ahmed Nematallah;Chang Hyun Park;David Black-Schaffer
With DRAM latencies increasing relative to CPU speeds, the performance of caches has become more important. This has led to increasingly sophisticated replacement policies that require complex calculations to update their replacement metadata, which often require multiple cycles. To minimize the negative impact of these metadata updates, architects have focused on policies that incur as little update latency as possible through a combination of reducing the policies’ precision and using parallel hardware. In this work we investigate whether these tradeoffs to reduce cache metadata update latency are needed. Specifically, we look at the performance and energy impact of increasing the latency of cache replacement policy updates. We find that even dramatic increases in replacement policy update latency have very limited effect. This indicates that designers have far more freedom to increase policy complexity and latency than previously assumed.
{"title":"Exploring the Latency Sensitivity of Cache Replacement Policies","authors":"Ahmed Nematallah;Chang Hyun Park;David Black-Schaffer","doi":"10.1109/LCA.2023.3296251","DOIUrl":"10.1109/LCA.2023.3296251","url":null,"abstract":"With DRAM latencies increasing relative to CPU speeds, the performance of caches has become more important. This has led to increasingly sophisticated replacement policies that require complex calculations to update their replacement metadata, which often require multiple cycles. To minimize the negative impact of these metadata updates, architects have focused on policies that incur as little update latency as possible through a combination of reducing the policies’ precision and using parallel hardware. In this work we investigate whether these tradeoffs to reduce cache metadata update latency are needed. Specifically, we look at the performance and energy impact of increasing the latency of cache replacement policy updates. We find that even dramatic increases in replacement policy update latency have very limited effect. This indicates that designers have far more freedom to increase policy complexity and latency than previously assumed.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"22 2","pages":"93-96"},"PeriodicalIF":2.3,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43674521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The demand for accurate information about the internal structure and characteristics of DRAM has been on the rise. Recent studies have explored the structure and characteristics of DRAM to improve processing in memory, enhance reliability, and mitigate a vulnerability known as rowhammer. However, DRAM manufacturers only disclose limited information through official documents, making it difficult to find specific information about actual DRAM devices. This paper presents reliable findings on the internal structure and characteristics of DRAM using activate-induced bitflips (AIBs), retention time test, and row-copy operation. While previous studies have attempted to understand the internal behaviors of DRAM devices, they have only shown results without identifying the causes or have analyzed DRAM modules rather than individual chips. We first uncover the size, structure, and operation of DRAM subarrays and verify our findings on the characteristics of DRAM. Then, we correct misunderstood information related to AIBs and demonstrate experimental results supporting the cause of rowhammer.
{"title":"X-ray: Discovering DRAM Internal Structure and Error Characteristics by Issuing Memory Commands","authors":"Hwayong Nam;Seungmin Baek;Minbok Wi;Michael Jaemin Kim;Jaehyun Park;Chihun Song;Nam Sung Kim;Jung Ho Ahn","doi":"10.1109/LCA.2023.3296153","DOIUrl":"10.1109/LCA.2023.3296153","url":null,"abstract":"The demand for accurate information about the internal structure and characteristics of DRAM has been on the rise. Recent studies have explored the structure and characteristics of DRAM to improve processing in memory, enhance reliability, and mitigate a vulnerability known as rowhammer. However, DRAM manufacturers only disclose limited information through official documents, making it difficult to find specific information about actual DRAM devices. This paper presents reliable findings on the internal structure and characteristics of DRAM using activate-induced bitflips (AIBs), retention time test, and row-copy operation. While previous studies have attempted to understand the internal behaviors of DRAM devices, they have only shown results without identifying the causes or have analyzed DRAM modules rather than individual chips. We first uncover the size, structure, and operation of DRAM subarrays and verify our findings on the characteristics of DRAM. Then, we correct misunderstood information related to AIBs and demonstrate experimental results supporting the cause of rowhammer.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"22 2","pages":"89-92"},"PeriodicalIF":2.3,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49364167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-03DOI: 10.1109/LCA.2023.3290427
Ipoom Jeong;Jiaqi Lou;Yongseok Son;Yongjoo Park;Yifan Yuan;Nam Sung Kim
The advancement in I/O technology has posed an unprecedented demand for high-performance processing on I/O data, leading to the development of Data Direct I/O (DDIO) technology. DDIO improves I/O processing efficiency by directly injecting all inbound I/O data into the last-level cache (LLC) in cooperation with any type of I/O device. Nonetheless, in certain scenarios with more than one I/O applications, DDIO may have sub-optimal performance caused by interference inside the LLC, resulting in the degradation of system performance. Especially, in this paper, we demonstrate that storage I/O on modern high-performance NVMe SSDs hardly benefits from DDIO, sometimes causing inefficient use of the shared LLC due to the “leaky DMA problem”. To address this problem, we propose LADIO , an adaptive approach that mitigates inter-application interference by dynamically controlling the DDIO functionality and reallocating LLC ways based on the leakage and locality of storage I/O data, respectively. In scenarios with heavy I/O interference, LADIO improves the throughput of network-intensive applications by 20% while maintaining that of storage-intensive applications.
随着I/O技术的进步，对高性能的I/O数据处理提出了前所未有的要求，导致了DDIO (data Direct I/O)技术的发展。DDIO通过与任何类型的I/O设备合作，直接将所有入站I/O数据注入最后一级缓存(LLC)，从而提高了I/O处理效率。尽管如此，在某些具有多个I/O应用程序的场景中，由于LLC内部的干扰，DDIO的性能可能不太理想，从而导致系统性能下降。特别是，在本文中，我们证明了现代高性能NVMe ssd上的存储I/O很难从DDIO中受益，有时由于“泄漏DMA问题”导致共享LLC的低效使用。为了解决这个问题，我们提出了LADIO，这是一种自适应方法，通过动态控制DDIO功能和根据存储I/O数据的泄漏和局域性重新分配LLC方式来减轻应用程序间的干扰。在有严重I/O干扰的场景中，radio在保持存储密集型应用的吞吐量的同时，将网络密集型应用的吞吐量提高20%。
{"title":"LADIO: Leakage-Aware Direct I/O for I/O-Intensive Workloads","authors":"Ipoom Jeong;Jiaqi Lou;Yongseok Son;Yongjoo Park;Yifan Yuan;Nam Sung Kim","doi":"10.1109/LCA.2023.3290427","DOIUrl":"10.1109/LCA.2023.3290427","url":null,"abstract":"The advancement in I/O technology has posed an unprecedented demand for high-performance processing on I/O data, leading to the development of Data Direct I/O (DDIO) technology. DDIO improves I/O processing efficiency by directly injecting all inbound I/O data into the last-level cache (LLC) in cooperation with any type of I/O device. Nonetheless, in certain scenarios with more than one I/O applications, DDIO may have sub-optimal performance caused by interference inside the LLC, resulting in the degradation of system performance. Especially, in this paper, we demonstrate that storage I/O on modern high-performance NVMe SSDs hardly benefits from DDIO, sometimes causing inefficient use of the shared LLC due to the “leaky DMA problem”. To address this problem, we propose \u0000<monospace>LADIO</monospace>\u0000, an adaptive approach that mitigates inter-application interference by dynamically controlling the DDIO functionality and reallocating LLC ways based on the leakage and locality of storage I/O data, respectively. In scenarios with heavy I/O interference, \u0000<monospace>LADIO</monospace>\u0000 improves the throughput of network-intensive applications by 20% while maintaining that of storage-intensive applications.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"22 2","pages":"77-80"},"PeriodicalIF":2.3,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48507765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-28DOI: 10.1109/LCA.2023.3290197
Hwanjun Lee;Seunghak Lee;Yeji Jung;Daehoon Kim
New memory interconnect technology, such as Intel's Compute Express Link (CXL), helps to expand memory bandwidth and capacity by adding CPU-less NUMA nodes to the main memory system, addressing the growing memory wall challenge. Consequently, modern computing systems embrace the heterogeneity in memory systems, composing the memory systems with a tiered memory system with near and far memory (e.g., local DRAM and CXL-DRAM). However, adopting NUMA interleaving, which can improve performance by exploiting node-level parallelism and utilizing aggregate bandwidth, to the tiered memory systems can face challenges due to differences in the access latency between the two types of memory, leading to potential performance degradation for memory-intensive workloads. By tackling the challenges, we first investigate the effects of the NUMA interleaving on the performance of the tiered memory systems. We observe that while NUMA interleaving is essential for applications demanding high memory bandwidth, it can negatively impact the performance of applications demanding low memory bandwidth. Next, we propose a dynamic cache management, called T-CAT , which partitions the last-level cache between near and far memory, aiming to mitigate performance degradation by accessing far memory. T-CAT attempts to reduce the difference in the average access latency between near and far memory by re-sizing the cache partitions. Through dynamic cache management, T-CAT can preserve the performance benefits of NUMA interleaving while mitigating performance degradation by the far memory accesses. Our experimental results show that T-CAT improves performance by up to 17% compared to cases with NUMA interleaving without the cache management.
{"title":"T-CAT: Dynamic Cache Allocation for Tiered Memory Systems With Memory Interleaving","authors":"Hwanjun Lee;Seunghak Lee;Yeji Jung;Daehoon Kim","doi":"10.1109/LCA.2023.3290197","DOIUrl":"10.1109/LCA.2023.3290197","url":null,"abstract":"New memory interconnect technology, such as Intel's Compute Express Link (CXL), helps to expand memory bandwidth and capacity by adding CPU-less NUMA nodes to the main memory system, addressing the growing memory wall challenge. Consequently, modern computing systems embrace the heterogeneity in memory systems, composing the memory systems with a tiered memory system with near and far memory (e.g., local DRAM and CXL-DRAM). However, adopting NUMA interleaving, which can improve performance by exploiting node-level parallelism and utilizing aggregate bandwidth, to the tiered memory systems can face challenges due to differences in the access latency between the two types of memory, leading to potential performance degradation for memory-intensive workloads. By tackling the challenges, we first investigate the effects of the NUMA interleaving on the performance of the tiered memory systems. We observe that while NUMA interleaving is essential for applications demanding high memory bandwidth, it can negatively impact the performance of applications demanding low memory bandwidth. Next, we propose a dynamic cache management, called \u0000<monospace>T-CAT</monospace>\u0000, which partitions the last-level cache between near and far memory, aiming to mitigate performance degradation by accessing far memory. \u0000<monospace>T-CAT</monospace>\u0000 attempts to reduce the difference in the average access latency between near and far memory by re-sizing the cache partitions. Through dynamic cache management, \u0000<monospace>T-CAT</monospace>\u0000 can preserve the performance benefits of NUMA interleaving while mitigating performance degradation by the far memory accesses. Our experimental results show that \u0000<monospace>T-CAT</monospace>\u0000 improves performance by up to 17% compared to cases with NUMA interleaving without the cache management.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"22 2","pages":"73-76"},"PeriodicalIF":2.3,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48978905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-28DOI: 10.1109/LCA.2023.3289515
Kiseok Jeon;Junghee Lee;Bumsoo Kim;James J. Kim
As the value of Bitcoin increases, the difficulty level of mining keeps increasing. This is generally addressed with application-specific integrated circuits (ASIC), but block candidates are still created by the software. The overhead of block candidate generation is relatively growing because the hash computation is boosted by ASIC. Additionally, it is getting harder to find the target nonce; If it is not found for a block candidate, a new block candidate must be generated. A new candidate can be generated to reduce the overhead of block candidate generation by modifying the coinbase without selecting and verifying transactions again. To this end, we propose a hardware accelerator for generating Merkle trees efficiently. The hash computation for Merkle tree generation is conducted with ASIC to reduce the overhead of block candidate generation, and the tree with only the modified coinbase is rapidly regenerated by reusing the intermediate results of the previously generated tree. Our simulation results demonstrate that the execution time can be reduced by up to 98.92% and power consumption by up to 99.73% when the number of transactions in a tree is 2048.
{"title":"Hardware Accelerated Reusable Merkle Tree Generation for Bitcoin Blockchain Headers","authors":"Kiseok Jeon;Junghee Lee;Bumsoo Kim;James J. Kim","doi":"10.1109/LCA.2023.3289515","DOIUrl":"10.1109/LCA.2023.3289515","url":null,"abstract":"As the value of Bitcoin increases, the difficulty level of mining keeps increasing. This is generally addressed with application-specific integrated circuits (ASIC), but block candidates are still created by the software. The overhead of block candidate generation is relatively growing because the hash computation is boosted by ASIC. Additionally, it is getting harder to find the target nonce; If it is not found for a block candidate, a new block candidate must be generated. A new candidate can be generated to reduce the overhead of block candidate generation by modifying the coinbase without selecting and verifying transactions again. To this end, we propose a hardware accelerator for generating Merkle trees efficiently. The hash computation for Merkle tree generation is conducted with ASIC to reduce the overhead of block candidate generation, and the tree with only the modified coinbase is rapidly regenerated by reusing the intermediate results of the previously generated tree. Our simulation results demonstrate that the execution time can be reduced by up to 98.92% and power consumption by up to 99.73% when the number of transactions in a tree is 2048.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"22 2","pages":"69-72"},"PeriodicalIF":2.3,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41591979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In-storage processing (ISP) efficiently examines large datasets but faces performance and security challenges. We introduce DockerSSD, a flexible ISP model that runs various applications near flash without modification. It employs lightweight OS-level virtualization in modern SSDs for faster ISP and better storage intelligence with a high flexiblity. DockerSSD reuses existing Docker container images for real-time data processing without altering the storage interface or runtime. Our design includes a new communication method and virtual firmware, alongside automated container-related network and I/O handling hardware. DockerSSD achieves a 2× speed improvement and reduces system-level power by 35.7%, on average.
{"title":"Containerized In-Storage Processing Model and Hardware Acceleration for Fully-Flexible Computational SSDs","authors":"Donghyun Gouk, Miryeong Kwon, Hanyeoreum Bae, Myoungsoo Jung","doi":"10.1109/lca.2023.3289828","DOIUrl":"https://doi.org/10.1109/lca.2023.3289828","url":null,"abstract":"In-storage processing (ISP) efficiently examines large datasets but faces performance and security challenges. We introduce DockerSSD, a flexible ISP model that runs various applications near flash without modification. It employs lightweight OS-level virtualization in modern SSDs for faster ISP and better storage intelligence with a high flexiblity. DockerSSD reuses existing Docker container images for real-time data processing without altering the storage interface or runtime. Our design includes a new communication method and virtual firmware, alongside automated container-related network and I/O handling hardware. DockerSSD achieves a 2× speed improvement and reduces system-level power by 35.7%, on average.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"26 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.1109/LCA.2023.3289710
Fernando Mosquera;Krishna Kavi;Gayatri Mehta;Lizy John
Microarchitectural innovations such as deep cache hierarchies, out-of-order execution, branch prediction and speculative execution have made possible the design of processors that meet ever-increasing demands for performance. However, these innovations have inadvertently introduced vulnerabilities, which are exploited by side-channel attacks and attacks relying on speculative executions. Mitigating the attacks while preserving the performance has been a challenge. In this letter we present an approach to obfuscate cache timing, making it more difficult for side-channel attacks to succeed. We create false cache hits using a small Guard Cache with randomization, and false cache misses by randomly evicting cache lines. We show that our false hits and false misses cause very minimal performance penalties and our obfuscation can make it difficult for common side-channel attacks such as Prime &Probe, Flush &Reload or Evict &Time to succeed.
{"title":"Guard Cache: Creating Noisy Side-Channels","authors":"Fernando Mosquera;Krishna Kavi;Gayatri Mehta;Lizy John","doi":"10.1109/LCA.2023.3289710","DOIUrl":"10.1109/LCA.2023.3289710","url":null,"abstract":"Microarchitectural innovations such as deep cache hierarchies, out-of-order execution, branch prediction and speculative execution have made possible the design of processors that meet ever-increasing demands for performance. However, these innovations have inadvertently introduced vulnerabilities, which are exploited by side-channel attacks and attacks relying on speculative executions. Mitigating the attacks while preserving the performance has been a challenge. In this letter we present an approach to obfuscate cache timing, making it more difficult for side-channel attacks to succeed. We create \u0000<italic>false cache hits</i>\u0000 using a small \u0000<italic>Guard Cache</i>\u0000 with randomization, and \u0000<italic>false cache misses</i>\u0000 by randomly evicting cache lines. We show that our \u0000<italic>false hits</i>\u0000 and \u0000<italic>false misses</i>\u0000 cause very minimal performance penalties and our obfuscation can make it difficult for common side-channel attacks such as Prime &Probe, Flush &Reload or Evict &Time to succeed.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"22 2","pages":"97-100"},"PeriodicalIF":2.3,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41685733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：