{"title":"An Integrated MaxFit Genetic Algorithm-SPICE Framework for 2-Stage Op-Amp Design Automation","authors":"V. HarshaM., B. Harish","doi":"10.1109/ISVLSI.2018.00040","DOIUrl":"https://doi.org/10.1109/ISVLSI.2018.00040","url":null,"abstract":"The Electronic Design Automation (EDA) tools have achieved high degree of maturity and reliability over the years for digital design. The design of analog circuits is a challenge attributed to the existence of multi-dimensional tradeoffs among multiple analog performance metrics like gain, bandwidth, power dissipation, supply voltage, input/output impedances, linearity, voltage swings and noise. The analog design proves to be a significant bottleneck in a System on Chip (SoC) implementation due to lack of automation techniques. To address this issue, the algorithms of the functioning of human brain or soft computing techniques can be gainfully deployed. This work proposes an integrated MaxFit Genetic Algorithm (GA) and GA-SPICE framework to achieve multi-objective optimization of analog design automation. The design of two-stage op-amp is demonstrated in this framework to optimize the objectives of open-loop DC gain, phase margin, unity gain-bandwidth, slew rate, power dissipation and area. The design is performed by proposed MaxFit GA programming of op-amp design equations in MATLAB environment and the design is transmitted seamlessly to LTspice to perform SPICE simulations for design verification. The dynamic fitness evaluation on SPICE generated performance metrics at each iteration of GA programming by transmitting them to MATLAB environment enhances the robustness of analog design significantly.","PeriodicalId":114330,"journal":{"name":"2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117089405","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":"Logic Synthesis for In-memory Computing Using Resistive Memories","authors":"S. Shirinzadeh, R. Drechsler","doi":"10.1109/ISVLSI.2018.00075","DOIUrl":"https://doi.org/10.1109/ISVLSI.2018.00075","url":null,"abstract":"The increasing urge to bypass the issue of the memory bottleneck in the current computer architectures has attracted high attention to in-memory computing enabled by emerging memory technologies such as Resistive Random Access Memory (RRAM). This paper studies in-memory computing from two perspectives, i.e. customized and instruction-based. The customized approach exploits logic representations to synthesize for in-memory computing. The approach proposes design methodologies and optimization algorithms for each representation with respect to area and latency upon the realizations of their logic primitives. The instruction-based approach proposes an automatic compiler to execute instructions on a logic-in-memory computer architecture and optimizes the programs. Experimental results for both approaches reveal considerable improvements compared to the state-of-the-art.","PeriodicalId":114330,"journal":{"name":"2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129454839","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}
Chenghong Wang, Zeinab S. Jalali, Caiwen Ding, Yanzhi Wang, S. Soundarajan
{"title":"A Fast and Effective Memristor-Based Method for Finding Approximate Eigenvalues and Eigenvectors of Non-negative Matrices","authors":"Chenghong Wang, Zeinab S. Jalali, Caiwen Ding, Yanzhi Wang, S. Soundarajan","doi":"10.1109/ISVLSI.2018.00108","DOIUrl":"https://doi.org/10.1109/ISVLSI.2018.00108","url":null,"abstract":"Throughout many scientific and engineering fields, including control theory, quantum mechanics, advanced dynamics, and network theory, a great many important applications rely on the spectral decomposition of matrices. Traditional methods such as the power iteration method, Jacobi eigenvalue method, and QR decomposition are commonly used to compute the eigenvalues and eigenvectors of a square and symmetric matrix. However, these methods suffer from certain drawbacks: in particular, the power iteration method can only find the leading eigen-pair (i.e., the largest eigenvalue and its corresponding eigenvector), while the Jacobi and QR decomposition methods face significant performance limitations when facing with large scale matrices. Typically, even producing approximate eigenpairs of a general square matrix requires at least O(N^3) time complexity, where N is the number of rows of the matrix. In this work, we exploit the newly developed memristor technology to propose a low-complexity, scalable memristorbased method for deriving a set of dominant eigenvalues and eigenvectors for real symmetric non-negative matrices. The time complexity for our proposed algorithm is O(N^2/Δ) (where Δ governs the accuracy). We present experimental studies to simulate the memristor-supporting algorithm, with results demonstrating that the average error for our method is within 4%, while its performance is up to 1.78X better than traditional methods.","PeriodicalId":114330,"journal":{"name":"2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130230649","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}
Yongfu Li, I. Tseng, Zhao Chuan Lee, V. Perez, Vikas Tripathi, Y. Ong
{"title":"Identifying Lithography Weak-Points of Standard Cells with Partial Pattern Matching","authors":"Yongfu Li, I. Tseng, Zhao Chuan Lee, V. Perez, Vikas Tripathi, Y. Ong","doi":"10.1109/ISVLSI.2018.00082","DOIUrl":"https://doi.org/10.1109/ISVLSI.2018.00082","url":null,"abstract":"At advanced process nodes, lithography weak-points can act as major factors of yield losses in manufactured integrated circuits, especially under aggressive design rules. Thus, it is desirable to consider potential lithography weak-point issues during the phase of designing standard cells in order to improve manufacturability of integrated circuits. In this paper, we propose a partial pattern matching methodology, which is based on the use of a combinatorial K-partitioning technique, to identify all of potential lithography weak-points for standard cells in a given standard cell library. In addition, the proposed methodology adopts a pruning technique to minimize false violations, and uses a prioritization technique to prioritize tasks of modifying and/or redesigning standard cells. Compared with a conventional placement-and-routing based methodology, our experimental results show that the proposed methodology can accurately detect more potential lithography weak-points.","PeriodicalId":114330,"journal":{"name":"2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121338696","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":"Parametric Circuit Optimization with Reinforcement Learning","authors":"Changcheng Tang, Zuochang Ye, Yan Wang","doi":"10.1109/ISVLSI.2018.00045","DOIUrl":"https://doi.org/10.1109/ISVLSI.2018.00045","url":null,"abstract":"In this paper, we focus on solving parametric optimization problems. Such kind of problems is very commonly seen in reality. We propose an efficient method to train a model that connects the solution to the parameters and thus solve all the problems with the same structure and different parameters at the same time. During the training process, instead of solving a series of optimization problems with randomly sampled w independently, we adopt reinforcement learning to accelerate the training process. Two networks are trained alternately. The first network is a value network, and it is trained to fit the target loss function. The second network is a policy network, whose output is connected to the input of the value network and it is trained to minimize the output of the value network. Experiments demonstrate the effectiveness of the proposed method.","PeriodicalId":114330,"journal":{"name":"2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127064842","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":"Accurate Models for Optimizing Tapered Microchannel Heat Sinks in 3D ICs","authors":"L. Hwang, B. Kwon, Martin D. F. Wong","doi":"10.1109/ISVLSI.2018.00021","DOIUrl":"https://doi.org/10.1109/ISVLSI.2018.00021","url":null,"abstract":"High-performance computing systems, especially 3D ICs, are yet facing thermal exacerbation. Inter-tier liquid cooling microchannel layers have been introduced into 3D ICs as an integrated cooling mechanism to tackle thermal degradation. Many research works optimize microchannel designs based on runtime-expensive numerical simulations or inaccurate thermofluid models. In this work, we propose accurate closed-form models on tapered microchannel to capture the relationship between channel geometry and heat transfer performance. To improve the accuracy, our correlation is based on developing flow model and derived from numerical simulation using a subset of multiple channel parameters. Our models reduce error by 57 % in Nusselt number and 45 % in pressure drop for channels with inlet width 100-400µm compared to commonly used fully developed flow based models in optimization. Obtained correlations show potential as solid foundation to achieve close to optimal design through runtime-efficient microchannel design optimization.","PeriodicalId":114330,"journal":{"name":"2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121509697","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":"Development of High-Stability, Low-Leakage 6Tr-SRAM with Single Data Line and Single Power Supply Using SOTB Process","authors":"S. Miyamoto, Nobuaki Kobayashi","doi":"10.1109/ISVLSI.2018.00077","DOIUrl":"https://doi.org/10.1109/ISVLSI.2018.00077","url":null,"abstract":"This paper proposes a single data line, double-word line 6Tr-SRAM for use in Internet of Things (IoT) devices using a silicon-on-thin-BOX (SOTB) process to achieve a high reliability and a low power consumption. The layout area was reduced compared to a conventional 6Tr structure by using a uniform data line. The proposed SRAM is able to generate multiple electric potentials without the need for additional power sources by employing a self-controllable voltage level (SVL) circuit, which is a simplified form of a DC/DC converter. Further, it expands the operating margin for writes and reads by decreasing the memory-cell supply voltage and increasing the memory-cell supply ground voltage in writes, and by dropping the word line potential when reading. When the variance of the threshold (Vt) was 0 (TT) and the power supply voltage (VDD) was 1.2 V, the read and write margins expanded by multiples of 2.09 and 1.31 of the conventional 6Tr SRAM, respectively. The standby power caused by a leakage when data is being saved under the same conditions was reduced to 9.17% of that of the conventional SRAM. The area overhead the SVL circuit was 1.383% of that of the conventional form.","PeriodicalId":114330,"journal":{"name":"2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127870543","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}
Cunxi Yu, Heinz Riener, Francesca Stradolini, G. Micheli
{"title":"Generating Safety Guidance for Medical Injection with Three-Compartment Pharmacokinetics Model","authors":"Cunxi Yu, Heinz Riener, Francesca Stradolini, G. Micheli","doi":"10.1109/ISVLSI.2018.00062","DOIUrl":"https://doi.org/10.1109/ISVLSI.2018.00062","url":null,"abstract":"Medical cyber-physical systems are a new trend of software controlled physical systems that are increasingly common in medical domains. With rapid developments in medical science and computer technology, safety verification and simulation becomes more challenging. This paper introduces a general model for medical injection systems, which can be used for formal verification, simulation/testing, and computing the Area Under the Curve (AUC) metrics, using Satisfiability Modulo Theories (SMT) over Reals. An algorithm of computing constrained AUC for measuring drug exposure with relative baseline, is presented based on the proof of unsatisfiability. We demonstrate that our model can efficiently solve these problems using the state-of-the-art SMT solver dReal.","PeriodicalId":114330,"journal":{"name":"2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129125948","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}
Xinyi Zhang, Clay Patterson, Yongpan Liu, Chengmo Yang, C. Xue, J. Hu
{"title":"Low Overhead Online Checkpoint for Intermittently Powered Non-volatile FPGAs","authors":"Xinyi Zhang, Clay Patterson, Yongpan Liu, Chengmo Yang, C. Xue, J. Hu","doi":"10.1109/ISVLSI.2018.00052","DOIUrl":"https://doi.org/10.1109/ISVLSI.2018.00052","url":null,"abstract":"Energy harvesting is an attractive way to power future IoT devices since it can eliminate the need for battery or power cables. However, harvested energy is intrinsically unstable. While FPGAs have been widely adopted in various embedded systems, it is hard to survive unstable power since all the memory components in FPGA are based on volatile SRAMs. The emerging non-volatile memory based FPGAs provide promising potentials to keep configuration data during power outages. However, few works have considered implementing efficient runtime intermediate data checkpoint on non-volatile FPGAs. To realize accumulative computation under intermittent power on FPGA, this paper proposes a low-cost design, FC-FPGAs, which utilizes \"scan-chain like\" flip-flops to track intermediate data. Instead of keeping all on-chip intermediate data, FC-FPGA only targets on necessary data that is labeled by off-line analysis and identified by an on-line tracking circuit. The evaluation shows that compared with state-of-the-art, FC-FPGA can realize accumulative computing and significantly reduce computation time and energy over a wide range of unstable power traces.","PeriodicalId":114330,"journal":{"name":"2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133623359","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}