{"title":"Machine Learning for Design Space Exploration and Optimization of Manycore Systems","authors":"R. Kim, J. Doppa, P. Pande","doi":"10.1145/3240765.3243483","DOIUrl":"https://doi.org/10.1145/3240765.3243483","url":null,"abstract":"In the emerging data-driven science paradigm, computing syStems ranging from IoT and mobile to manycores and datacenters play distinct roles. These systems need to be optimized for the objectives and constraints dictated by the needs of the application. In this paper, we describe how machine learning techniques can be leveraged to improve the computational-efficiency of hardware design optimization. This includes generic methodologies that are applicable for any hardware design space. As an example, we discuss a guided design space exploration framework to accelerate application-specific manycore systems design and advanced imitation learning techniques to improve on-chip resource management. We present some experimental results for application-specific manycore system design optimization and dynamic power management to demonstrate the efficacy of these methods over traditional EDA approaches.","PeriodicalId":413037,"journal":{"name":"2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127290495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Scalable-Effort ConvNets for Multilevel Classification","authors":"Valentino Peluso, A. Calimera","doi":"10.1145/3240765.3240845","DOIUrl":"https://doi.org/10.1145/3240765.3240845","url":null,"abstract":"This work introduces the concept of scalable-effort Convolutional Neural Networks (ConvNets), an effort-accuracy scalable model for classification of data at multilevel abstraction. Scalable-effort ConvNets are able to adapt at run-time to the complexity of the classification problem, i.e. the level of abstraction defined by the application (or context), and reach a given classification accuracy with minimal computational effort. The mechanism is implemented using a single-weight scalable-precision model rather than an ensemble of quantized weight models; this makes the proposed strategy highly flexible and particularly suited for embedded architectures with limited resource availability. The paper describes (i) a hardware/software vertical implementation of scalable-precision multiply&accumulate arithmetic, (ii) an accuracy-constrained heuristic that delivers near-optimal layer-by-layer precision mapping at a predefined level of abstraction. It also reports the validation for three state-of-the-art nets, i.e. AlexNet, SqueezeNet and MobileNet, trained and tested with ImageNet. Collected results show scalable-effort ConvNets guarantee flexibility and substantial savings: 47.07% computational effort reduction at minimum accuracy, or 30.6% accuracy improvement at maximum effort w.r.t. standard flat ConvNets (average over the three benchmarks for high-level classification).","PeriodicalId":413037,"journal":{"name":"2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"367 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121735156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Macro-Aware Row-Style Power Delivery Network Design for Better Routability","authors":"Jai-Ming Lin, Jhih-Sheng Syu, I-Ru Chen","doi":"10.1145/3240765.3240824","DOIUrl":"https://doi.org/10.1145/3240765.3240824","url":null,"abstract":"Reliability of a P/G network is one of the most important concerns in a chip design, which makes powerplanning the most critical step in the physical design. Traditional P/G network design mainly focuses on reducing usage of routing resource to satisfy voltage drop and electromigration constraints according to a regular mesh. As the number of macros in a modern design increases, this style may waste more routing resource and make routing congestion more severe in local regions. In order to save routing resource and increase routability, this paper proposes a delicate powerplanning method. First, we propose a row-style power mesh to facilitate connection of pre-placed macros and increase routability of signal nets in the later stage. Besides, an effective power stripe width which can reduce wastage of routing resource and provide stronger supply voltage is found. Moreover, we propose the first work to use the linear programming algorithm to minimize P/G routing area and consider routability at the same time. The experimental results show that routability of a design with many macros can be significantly improved by our row-style power networks.","PeriodicalId":413037,"journal":{"name":"2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129692006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Safety and Security Architecture for Reducing Accidents in Intelligent Transportation Systems","authors":"Qian Chen, A. Sowan, Shouhuai Xu","doi":"10.1145/3240765.3243462","DOIUrl":"https://doi.org/10.1145/3240765.3243462","url":null,"abstract":"The Internet of Things (IoT) technology is transforming the world into Smart Cities, which have a huge impact on future societal lifestyle, economy and business. Intelligent Transportation Systems (ITS), especially IoT-enabled Electric Vehicles (EVs), are anticipated to be an integral part of future Smart Cities. Assuring ITS safety and security is critical to the success of Smart Cities because human lives are at stake. The state-of-the-art understanding of this matter is very superficial because there are many new problems that have yet to be investigated. For example, the cyber-physical nature of ITS requires considering human-in-the-loop (i.e., drivers and pedestrians) and imposes many new challenges. In this paper, we systematically explore the threat model against ITS safety and security (e.g., malfunctions of connected EVs/transportation infrastructures, driver misbehavior and unexpected medical conditions, and cyber attacks). Then, we present a novel and systematic ITS safety and security architecture, which aims to reduce accidents caused or amplified by a range of threats. The architecture has appealing features: (i) it is centered at proactive cyber-physical-human defense; (ii) it facilitates the detection of early-warning signals of accidents; (iii) it automates effective defense against a range of threats.","PeriodicalId":413037,"journal":{"name":"2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"35 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134041888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enabling Deep Learning at the LoT Edge","authors":"Liangzhen Lai, Naveen Suda","doi":"10.1145/3240765.3243473","DOIUrl":"https://doi.org/10.1145/3240765.3243473","url":null,"abstract":"Deep learning algorithms have demonstrated super-human capabilities in many cognitive tasks, such as image classification and speech recognition. As a result, there is an increasing interest in deploying neural networks (NNs) on low-power processors found in always-on systems, such as those based on Arm Cortex-M microcontrollers. In this paper, we discuss the challenges of deploying neural networks on microcontrollers with limited memory, compute resources and power budgets. We introduce CMSIS-NN, a library of optimized software kernels to enable deployment of NNs on Cortex-M cores. We also present techniques for NN algorithm exploration to develop light-weight models suitable for resource constrained systems, using keyword spotting as an example.","PeriodicalId":413037,"journal":{"name":"2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"29 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116641609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yen-Chun Fang, Heng-Yi Lin, Min-Yan Su, C. Li, Eric Jia-Wei Fang
{"title":"Machine-learning-based Dynamic IR Drop Prediction for ECO","authors":"Yen-Chun Fang, Heng-Yi Lin, Min-Yan Su, C. Li, Eric Jia-Wei Fang","doi":"10.1145/3240765.3240823","DOIUrl":"https://doi.org/10.1145/3240765.3240823","url":null,"abstract":"During design signoff, many iterations of Engineer Change Order (ECO) are needed to ensure IR drop of each cell instance meets the specified limit. It is a waste of resources because repeated dynamic IR drop simulations take a very long time on very similar designs. In this work, we train a machine learning model, based on data before ECO, and predict IR drop after ECO. To increase our prediction accuracy, we propose 17 timing-aware, power-aware, and physical-aware features. Our method is scalable because the feature dimension is fixed (937), independent of design size and cell library. Also, we propose to build regional models for cell instances near IR drop violations to improves both prediction accuracy and training time. Our experiments show that our prediction correlation coefficient is 0.97 and average error is 3.0mV on a 5-million-cell industry design. Our IR drop prediction for 100K cell instances can be completed within 2 minutes. Our proposed method provides a fast IR drop prediction to speedup ECO.","PeriodicalId":413037,"journal":{"name":"2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127095726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Fast Thermal-Aware Fixed-Outline Floorplanning Methodology Based on Analytical Models","authors":"Jai-Ming Lin, Tai-Ting Chen, Yen-Fu Chang, Wei-Yi Chang, Ya-Ting Shyu, Yeong-Jar Chang, Juin-Ming Lu","doi":"10.1145/3240765.3240769","DOIUrl":"https://doi.org/10.1145/3240765.3240769","url":null,"abstract":"High temperature or temperature non-uniformity have become a serious threat to performance and reliability of highperformance integrated circuits (ICs). Thermal effect becomes a non-ignorable issue to circuit design or physical design. To estimate temperature accurately, the locations of modules have to be determined, which makes an efficient and effective thermal-aware floorplanning play a more important role. To resolve this problem, this paper proposes a differential nonlinear model which can approximate temperature and minimize wirelength at the same time during floorplanning. We also apply some techniques such a thermal-aware clustering or shrinking hot modules in the multi-level framework to further reduce temperature without inducing longer wirelength. The experimental results demonstrate that temperature and wirelength are greatly improved in our method compared to other works. More importantly, our runtime is quite fast and the fixed-outline constraint is also satisfied.","PeriodicalId":413037,"journal":{"name":"2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126426673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Baixin Chen, Umamaheswara Rao Tida, Cheng Zhuo, Yiyu Shi
{"title":"Modeling and Optimization of Magnetic Core TSV-Inductor for On-Chip DC-DC Converter","authors":"Baixin Chen, Umamaheswara Rao Tida, Cheng Zhuo, Yiyu Shi","doi":"10.1145/3240765.3240829","DOIUrl":"https://doi.org/10.1145/3240765.3240829","url":null,"abstract":"Conventional on-chip spiral inductor consumes significant top metal routing area, thereby preventing its popularity in many on-chip applications. Recently TSV-inductor with a magnetic core has been proved to be a viable option for on-chip DC-DC converter in a 14nm test chip. The operating conditions of such inductors play a major role in maximizing the performance and efficiency of the DC-DC converter. However, due to its unique TSV-structure, unlike conventional spiral inductor, much of the modeling details remain unclear. This paper analyzes the modeling details of a magnetic core TSV-inductor and proposes a design methodology to optimize power losses of the inductor. With this methodology, designers can ensure fast and reliable inductor optimization for on-chip applications. Experimental results show that the optimized magnetic core TSV-inductor can achieve inductance density improvement of 6.0-7.7× and quality factor improvements of 1.3-1.6× while maintaining the same footprint.","PeriodicalId":413037,"journal":{"name":"2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115375562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sneak Path Free Reconfiguration of Via-switch Crossbars Based FPGA","authors":"Ryutaro Doi, Jaehoon Yu, M. Hashimoto","doi":"10.1145/3240765.3240849","DOIUrl":"https://doi.org/10.1145/3240765.3240849","url":null,"abstract":"FPGA that utilizes via-switches, which are a kind of nonvolatile resistive RAMs, for crossbar implementation is attracting attention due to higher integration density and performance. However, programming via-switches arbitrarily in a crossbar is not trivial since a programming current must be provided through signal wires that are shared by multiple via-switches. Consequently, depending on the previous programming status in sequential programming, unintentional switch programming may occur due to signal detour, which is called sneak path problem. This problem interferes the reconfiguration of via-switch FPGA, and hence countermeasures for sneak path problem are indispensable. This paper identifies the circuit status that causes sneak path problem and proposes a sneak path avoidance method that gives sneak path free programming order of via-switches in a crossbar. We prove that sneak path free programming order necessarily exists for arbitrary on-off patterns in a crossbar as long as no loops exist, and also validate the proof and the proposed method with simulation-based evaluation. Thanks to the proposed method, any practical configurations of via-switch FPGA can be successfully programmed without sneak path problem.","PeriodicalId":413037,"journal":{"name":"2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132344528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enhancing the Solution Quality of Hardware Ising-Model Solver via Parallel Tempering","authors":"Hidenori Gyoten, Masayuki Hiromoto, Takashi Sato","doi":"10.1145/3240765.3240806","DOIUrl":"https://doi.org/10.1145/3240765.3240806","url":null,"abstract":"We propose an efficient Ising processor with approximated parallel tempering (IPAPT) implemented on an FPGA. Hardware-friendly approximations of the components of parallel tempering (PT) are proposed to enhance solution quality with low hardware overhead. Multiple replicas of Ising states having different temperatures run in parallel by sharing a single network structure, and the replicas are exchanged based on the approximated energy evaluation. The application of PT substantially improves the quality of optimization solutions. The experimental results on the various max-cut problems have shown that utilization of PT significantly increases the probability of obtaining optimal solutions, and IPAPT obtains optimal solutions two orders magnitude faster than a software solver.","PeriodicalId":413037,"journal":{"name":"2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128744348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}