IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems最新文献

{"title":"Indoor–Outdoor Energy Management for Wearable IoT Devices With Conformal Prediction and Rollout","authors":"Nuzhat Yamin;Ganapati Bhat","doi":"10.1109/TCAD.2024.3448382","DOIUrl":"https://doi.org/10.1109/TCAD.2024.3448382","url":null,"abstract":"Internet of Things (IoT) devices have the potential to enable a wide range of applications, including smart health and agriculture. However, they are limited by their small battery capacities. Utilizing energy harvesting is a promising approach to augment the battery life of IoT devices. However, relying solely on harvested energy is insufficient due to the stochastic nature of ambient sources. Predicting and accounting for uncertainty in the energy harvest (EH) is critical for optimal energy management (EM) in wearable IoT devices. This article proposes a two-step uncertainty-aware EH prediction and management framework for wearable IoT devices. First, the framework employs an energy-efficient conformal prediction (CP) method to predict future EH and construct prediction intervals. Contrasting to prior CP approaches, we propose constructing the prediction intervals using a combination of residuals from previous hours and days. Second, the framework proposes a near-optimal EM approach that utilizes a rollout algorithm. The rollout algorithm efficiently simulates various energy allocation trajectories as a function of predicted EH bounds. Using results from the rollout, the proposed approach constructs energy allocation bounds that maximize application utility (quality of service) with a high probability. Evaluations using real-world energy data from ARAS and Mannheim datasets show that the proposed CP for EH prediction provides 93% coverage probability with an average width of 9.5 J and 1.9 J, respectively. Moreover, EM using the rollout algorithm provides energy allocation decisions that are within 1.9–2.9 J of the optimal with minimal overhead.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"43 11","pages":"3370-3381"},"PeriodicalIF":2.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595861","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}

{"title":"Meta-Scanner: Detecting Fault Attacks via Scanning FPGA Designs Metadata","authors":"Hassan Nassar;Jonas Krautter;Lars Bauer;Dennis Gnad;Mehdi Tahoori;Jörg Henkel","doi":"10.1109/TCAD.2024.3443769","DOIUrl":"https://doi.org/10.1109/TCAD.2024.3443769","url":null,"abstract":"With the rise of the big data, processing in the cloud has become more significant. One method of accelerating applications in the cloud is to use field programmable gate arrays (FPGAs) to provide the needed acceleration for the user-specific applications. Multitenant FPGAs are a solution to increase efficiency. In this case, multiple cloud users upload their accelerator designs to the same FPGA fabric to use them in the cloud. However, multitenant FPGAs are vulnerable to low-level denial-of-service attacks that induce excessive voltage drops using the legitimate configurations. Through such attacks, the availability of the cloud resources to the nonmalicious tenants can be hugely impacted, leading to downtime and thus financial losses to the cloud service provider. In this article, we propose a tool for the offline classification to identify which FPGA designs can be malicious during operation by analysing the metadata of the bitstream generation step. We generate and test 475 FPGA designs that include 38% malicious designs. We identify and extract five relevant features out of the metadata provided from the bitstream generation step. Using ten-fold cross-validation to train a random forest classifier, we achieve an average accuracy of 97.9%. This significantly surpasses the conservative comparison with the state-of-the-art approaches, which stands at 84.0%, as our approach detects stealthy attacks undetectable by the existing methods.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"43 11","pages":"3443-3454"},"PeriodicalIF":2.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595917","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}

{"title":"D-Linker: Debloating Shared Libraries by Relinking From Object Files","authors":"Jiatai He;Pengpeng Hou;Jiageng Yu;Ji Qi;Ying Sun;Lijuan Li;Ruilin Zhao;Yanjun Wu","doi":"10.1109/TCAD.2024.3446712","DOIUrl":"https://doi.org/10.1109/TCAD.2024.3446712","url":null,"abstract":"Shared libraries are widely used in software development to execute third-party functions. However, the size and complexity of shared libraries tend to increase with the need to support more features, resulting in bloated shared libraries. This leads to resource waste and security issues as a significant amount of generic functionality is included unnecessarily in most scenarios, especially in embedded systems. To address this issue, previous works attempt to debloat shared libraries through binary rewriting or recompilation. However, these works face a tradeoff between flexibility in usage (needs recompilation and runtime support) and the effectiveness of debloating (binary rewriting achieves insufficient file size reduction). We propose D-Linker, a tool that debloats shared libraries by reducing both code and data sections in link-time at the object level without recompilation. Our key insight is that object-level shared library debloating is especially suitable for embedded systems because it strikes a balance of flexibility and efficiency. D-Linker identifies the required ELF object files of the shared libraries in an application and relinks them to produce a debloated shared library with better-debloating effectiveness by avoiding the data reference analysis. Our approach achieves over 70% of gadgets reduction as a security benefit and an average size reduction of 49.6% for a stripped libc of coreutils. The results also indicate that D-Linker improves debloating effectiveness by approximately 30% compared to binary-level shared library debloating and incurs a 5% decrease in code gadgets reduction compared to source-code-level shared library debloating.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"43 11","pages":"3768-3779"},"PeriodicalIF":2.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595934","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}

{"title":"Modeling and Analysis of the LatestTime Message Synchronization Policy in ROS","authors":"Chenhao Wu;Ruoxiang Li;Naijun Zhan;Nan Guan","doi":"10.1109/TCAD.2024.3446709","DOIUrl":"https://doi.org/10.1109/TCAD.2024.3446709","url":null,"abstract":"Sensor fusion plays a critical role in modern robotics and autonomous systems. In reality, the sensor data destined for the fusion algorithm may have substantially different sampling times. Without proper management, this could lead to poor sensor fusion quality. Robot operating system (ROS) is the most popular robotic software framework, providing essential mechanisms for synchronizing messages to mitigate timing inconsistencies during sensor fusion. Recently, ROS introduced a new LatestTime message synchronization policy. In this article, we formally model the behavior of the LatestTime policy and analyze its worst-case real-time performance. Our investigation uncovers a defect of the LatestTime policy that may cause infinite latency in publishing subsequent outputs. We propose a solution to address this defect and develop safe and tight upper bounds on worst-case real-time performance, in terms of both the maximal temporal inconsistency of its outputs and the incurred latency. Experiments are conducted to evaluate the precision, safety and robustness of our theoretical results.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"43 11","pages":"3576-3587"},"PeriodicalIF":2.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595802","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}

{"title":"Time-Triggered Scheduling for Nonpreemptive Real-Time DAG Tasks Using 1-Opt Local Search","authors":"Sen Wang;Dong Li;Shao-Yu Huang;Xuanliang Deng;Ashrarul H. Sifat;Jia-Bin Huang;Changhee Jung;Ryan Williams;Haibo Zeng","doi":"10.1109/TCAD.2024.3442985","DOIUrl":"https://doi.org/10.1109/TCAD.2024.3442985","url":null,"abstract":"Modern real-time systems often involve numerous computational tasks characterized by intricate dependency relationships. Within these systems, data propagate through cause–effect chains from one task to another, making it imperative to minimize end-to-end latency to ensure system safety and reliability. In this article, we introduce innovative nonpreemptive scheduling techniques designed to reduce the worst-case end-to-end latency and/or time disparity for task sets modeled with directed acyclic graphs (DAGs). This is challenging because of the noncontinuous and nonconvex characteristics of the objective functions, hindering the direct application of standard optimization frameworks. Customized optimization frameworks aiming at achieving optimal solutions may suffer from scalability issues, while general heuristic algorithms often lack theoretical performance guarantees. To address this challenge, we incorporate the “1-opt” concept from the optimization literature (Essentially, 1-opt means that the quality of a solution cannot be improved if only one single variable can be changed) into the design of our algorithm. We propose a novel optimization algorithm that effectively balances the tradeoff between theoretical guarantees and algorithm scalability. By demonstrating its theoretical performance guarantees, we establish that the algorithm produces 1-opt solutions while maintaining polynomial run-time complexity. Through extensive large-scale experiments, we demonstrate that our algorithm can effectively reduce the latency metrics by 20% to 40%, compared to state-of-the-art methods.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"43 11","pages":"3650-3661"},"PeriodicalIF":2.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595814","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}

{"title":"Page Type-Aware Full-Sequence Program Scheduling via Reinforcement Learning in High Density SSDs","authors":"Jun Li;Zhigang Cai;Balazs Gerofi;Yutaka Ishikawa;Jianwei Liao","doi":"10.1109/TCAD.2024.3444718","DOIUrl":"https://doi.org/10.1109/TCAD.2024.3444718","url":null,"abstract":"Full-sequence program (FSP) can program multiple bits simultaneously, and thus complete a multiple-page write at one time for naturally enhancing write performance of high density 3-D solid-state drives (SSDs). This article proposes an FSP scheduling approach for the 3-D quad-level cell (QLC) SSDs, to further boost their read responsiveness. Considering each FSP operation in QLC SSDs spans \u0000<monospace>four</monospace>\u0000 different types of QLC pages having dissimilar read latency, we introduce matching four pages of application data to the suited QLC pages and flush them together with the one-shot program of FSP. To this end, we employ reinforcement learning to classify the (cached) application data into \u0000<monospace>four</monospace>\u0000 categories on the basis of their historical access frequency and the associating request size. Thus, the frequently read data can be mapped to the QLC pages having less access latency, meanwhile the other data can be flushed onto the slow QLC pages. Then, we can group four different categories of data pages and flush them together into a four-page unit of 3-D QLC SSDs with an FSP operation. In addition, a proactive rewrite method is also triggered for grouping the hot read data with the cached data to form an FSP unit. Through a series of emulation tests on several realistic disk traces, we show that the proposed mechanisms yields notable performance improvement on the read responsiveness.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"43 11","pages":"3696-3707"},"PeriodicalIF":2.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595816","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}

{"title":"GEAR: Graph-Evolving Aware Data Arranger to Enhance the Performance of Traversing Evolving Graphs on SCM","authors":"Wen-Yi Wang;Chun-Feng Wu;Yun-Chih Chen;Tei-Wei Kuo;Yuan-Hao Chang","doi":"10.1109/TCAD.2024.3447222","DOIUrl":"https://doi.org/10.1109/TCAD.2024.3447222","url":null,"abstract":"In the era of big data, social network services continuously modify social connections, leading to dynamic and evolving graph data structures. These evolving graphs, vital for representing social relationships, pose significant memory challenges as they grow over time. To address this, storage-class-memory (SCM) emerges as a cost-effective solution alongside DRAM. However, contemporary graph evolution processes often scatter neighboring vertices across multiple pages, causing weak graph spatial locality and high-TLB misses during traversals. This article introduces SCM-Based graph-evolving aware data arranger (GEAR), a joint management middleware optimizing data arrangement on SCMs to enhance graph traversal efficiency. SCM-based GEAR comprises multilevel page allocation, locality-aware data placement, and dual-granularity wear leveling techniques. Multilevel page allocation prevents scattering of neighbor vertices relying on managing each page in a finer-granularity, while locality-aware data placement reserves space for future updates, maintaining strong graph spatial locality. The dual-granularity wear leveler evenly distributes updates across SCM pages with considering graph traversing characteristics. Evaluation results demonstrate SCM-based GEAR’s superiority, achieving 23% to 70% reduction in traversal time compared to state-of-the-art frameworks.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"43 11","pages":"3674-3684"},"PeriodicalIF":2.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595858","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}

{"title":"OPIMA: Optical Processing-in-Memory for Convolutional Neural Network Acceleration","authors":"Febin Sunny;Amin Shafiee;Abhishek Balasubramaniam;Mahdi Nikdast;Sudeep Pasricha","doi":"10.1109/TCAD.2024.3446870","DOIUrl":"https://doi.org/10.1109/TCAD.2024.3446870","url":null,"abstract":"Recent advances in machine learning (ML) have spotlighted the pressing need for computing architectures that bridge the gap between memory bandwidth and processing power. The advent of deep neural networks has pushed traditional Von Neumann architectures to their limits due to the high latency and energy consumption costs associated with data movement between the processor and memory for these workloads. One of the solutions to overcome this bottleneck is to perform computation within the main memory through processing-in-memory (PIM), thereby limiting data movement and the costs associated with it. However, dynamic random-access memory-based PIM struggles to achieve high throughput and energy efficiency due to internal data movement bottlenecks and the need for frequent refresh operations. In this work, we introduce OPIMA, a PIM-based ML accelerator, architected within an optical main memory. OPIMA has been designed to leverage the inherent massive parallelism within main memory while performing high-speed, low-energy optical computation to accelerate ML models based on convolutional neural networks. We present a comprehensive analysis of OPIMA to guide design choices and operational mechanisms. In addition, we evaluate the performance and energy consumption of OPIMA, comparing it with conventional electronic computing systems and emerging photonic PIM architectures. The experimental results show that OPIMA can achieve \u0000<inline-formula> <tex-math>$2.98times $ </tex-math></inline-formula>\u0000 higher throughput and \u0000<inline-formula> <tex-math>$137times $ </tex-math></inline-formula>\u0000 better energy efficiency than the best known prior work.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"43 11","pages":"3888-3899"},"PeriodicalIF":2.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595076","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}

{"title":"Enhancing SRAM-Based PUF Reliability Through Machine Learning-Aided Calibration Techniques","authors":"Kuheli Pratihar;Soumi Chatterjee;Rajat Subhra Chakraborty;Debdeep Mukhopadhyay","doi":"10.1109/TCAD.2024.3449570","DOIUrl":"https://doi.org/10.1109/TCAD.2024.3449570","url":null,"abstract":"Static random access memory (SRAM)-based physically unclonable functions (PUFs) utilize unpredictable start-up values (SUVs) for key generation, making them widely adopted in cryptographic systems. This unpredictability in SUVs is accompanied by device noise that escalates with process-voltage–temperature (PVT) variations, resulting in significant deviations from the golden response collected at ambient conditions, thereby increasing the bit-error-rate (BER) of the PUF responses. To reduce this high-\u0000<inline-formula> <tex-math>$(geq 15%)$ </tex-math></inline-formula>\u0000 BER, either an involved error correcting code (ECC) circuitry with significant overhead is required, or more helper information needs to be generated at varying operating conditions, resulting in increased information leakage. We address this issue by proposing the first reported application of machine learning to recalibrate the responses by predicting the golden responses of the SRAM-based PUF (SRAM-PUF) at different operating conditions with high accuracy. Our recalibration technique is based on a novel collective decision that involves observing the neighborhood cells of the SRAM-PUF, as opposed to the traditional single-cell approach. By leveraging a memory map exhibiting a high correlation in ambient reliability amongst neighboring cells, we indirectly use the physical co-location of SRAM cells to assist neighborhood error prediction. It leads to efficient post-processing for SRAM-PUFs by using helper data generated at ambient conditions only while employing a fixed ECC designed for the same. Subsequently, to justify our claims and validate the efficacy of our proposed methodology, we demonstrate extensive experimentation results over multiple SRAM-PUF instances implemented on the Arduino UNO (an 8-bit microcontroller unit) and its scaled-up version, the Arduino Zero (a 32-bit microcontroller unit) boards, by varying supply voltages from 3.8 to 6.2 V and 7 to 12 V, respectively, and temperature from −25° to 70° C in both cases. Our observations show a vast drop in BER from 17.02% to \u0000<inline-formula> <tex-math>$approx 1%$ </tex-math></inline-formula>\u0000. Although worst-case conditions with both voltage and temperature variations at play resulted in a BER of 20%, using our proposed approach reduces it to \u0000<inline-formula> <tex-math>$approx 1{text {-}} 2%$ </tex-math></inline-formula>\u0000, in turn demonstrating the high efficacy of our scheme.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"43 11","pages":"3491-3502"},"PeriodicalIF":2.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595805","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}

{"title":"LightFS: A Lightweight Host-CSD Coordinated File System Optimizing for Heavy Small File Accesses","authors":"Jiali Li;Zhaoyan Shen;Duo Liu;Xianzhang Chen;Kan Zhong;Zhaoyang Zeng;Yujuan Tan","doi":"10.1109/TCAD.2024.3443010","DOIUrl":"https://doi.org/10.1109/TCAD.2024.3443010","url":null,"abstract":"Computational storage drive (CSD) improves the data processing efficiency by processing the data within the storage. However, existing CSDs rely on the host-centric file systems to manage the data, where the layouts of files are retrieved by the host and sent to the CSD, resulting in additional I/O overhead and reduced processing efficiency, especially in heavy small file accesses. Moreover, the lack of consistency mechanisms poses potential consistency issues. To address these challenges, we propose LightFS, a lightweight host-CSD coordinated file system for the CSD file management. To reduce task offloading overhead, LightFS builds an index file \u0000<inline-formula> <tex-math>$.ndpmeta$ </tex-math></inline-formula>\u0000 which summarizes the files’ metadata and shares between the host and CSD to enable CSD to retrieve the file layout in storage directly. To ensure consistency, LightFS employs a metadata locker and an update synchronizer. The metadata locker leverages the out-of-place update feature of the flash to capture a snapshot of the file to be written without any data copy, while the update synchronizer triggers metadata updates by monitoring the addresses of written blocks to ensure that the modified file is successfully written to the CSD. We implement and evaluate LightFS on a real testbed, and the results demonstrate that LightFS achieves \u0000<inline-formula> <tex-math>$3.66times $ </tex-math></inline-formula>\u0000 performance improvement on the average in real-world operations.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"43 11","pages":"3527-3538"},"PeriodicalIF":2.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595815","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}