A realistic early-stage power grid verification algorithm based on hierarchical constraints

Power grid verification has become an indispensable step to guarantee a functional and robust chip design. Vectorless power grid verification methods, by solving linear programming (LP) problems under current constraints, enable worst-case voltage drop predictions at an early stage of design when the specific waveforms of current drains are unknown. In this paper, a novel power grid verification algorithm based on hierarchical constraints is proposed. By introducing novel power constraints, the proposed algorithm generates more realistic current patterns and provides less pessimistic voltage drop predictions. The model order reduction-based coefficient computation algorithm reduces the complexity of formulating the LP problems from being proportional to steps to being independent of steps. Utilizing the special hierarchical constraint structure, the submodular polyhedron greedy algorithm dramatically reduces the complexity of solving the LP problems from over O(k 3 m) to roughly O(k k m), where k m is the number of variables. Numerical results have shown that the proposed algorithm provides less pessimistic voltage drop prediction while at the same time achieves dramatic speedup. © 2011 IEEE.published_or_final_versio

Power/Ground Networks Optimization Design Methods with Noise Immunity

制度:新 ; 報告番号:甲3535号 ; 学位の種類:博士(工学) ; 授与年月日:2012/3/15 ; 早大学位記番号:新587

A meta-heuristic method to design off-grid community electrification projects with renewable energies

The design of off-grid electrification projects considering hybrid systems and distribution microgrids is a complex task that requires the use of decision support tools. Most of existing tools focus on the design of hybrid systems without defining generator locations and microgrids configuration. Recently a deterministic heuristic was developed to solve the problem. In this study we present an enhanced deterministic heuristic and then a meta-heuristic procedure for designing community off-grid electrification projects based on renewable energies considering micro-scale resource variations and a combination of independent generation points and microgrids. Both new algorithms improve performance of the previous existing procedure. The new deterministic heuristic can rapidly (in a computational time lower than 1 min) obtain a good solution. On the other hand, the proposed meta-heuristic method considerably enhances solutions obtained by the deterministic heuristic with a computational time of 1 h on a standard PC. The improvement tends to raise as the complexity of the analyzed instance increases. The proposed algorithm is a complete design tool that can efficiently support the design of stand-alone community electrification projects requiring of low computational resourcesPeer ReviewedPostprint (author's final draft

On the deployment of on-chip noise sensors

The relentless technology scaling has led to significantly reduced noise margin and complicated functionalities. As such, design time techniques per se are less likely to ensure power integrity, resulting in runtime voltage emergencies. To alleviate the issue, recently several works have shed light on the possibilities of dynamic noise management systems. Most of these works rely on on-chip noise sensors to accurately capture voltage emergencies. However, they all assume that the placement of the sensors is given. It remains an open problem in the literature how to optimally place a given number of noise sensors for best voltage emergency detection. The problem of noise sensor placement is defined at first along with a novel sensing quality metric (SQM) to be maximized. The threshold voltage for noise sensors to report emergencies serves as a critical tuning knob between the system failure rate and false alarms. The problem of minimizing the system alarm rate subject to a given system failure rate constraint is formulated. It is further shown that with the help of IDDQ measurements during testing which reveal process variation information, it is possible and efficient to compute a per-chip optimal threshold voltage threshold. In the third chapter, a novel framework to predict the resonance frequency using existing on-chip noise sensors, based on the theory of 1-bit compressed sensing is proposed. The proposed framework can help to achieve the resonance frequency of individual chips so as to effectively avoid resonance noise at runtime --Abstract, page iii

Custom Cell Placement Automation for Asynchronous VLSI

Asynchronous Very-Large-Scale-Integration (VLSI) integrated circuits have demonstrated many advantages over their synchronous counterparts, including low power consumption, elastic pipelining, robustness against manufacturing and temperature variations, etc. However, the lack of dedicated electronic design automation (EDA) tools, especially physical layout automation tools, largely limits the adoption of asynchronous circuits. Existing commercial placement tools are optimized for synchronous circuits, and require a standard cell library provided by semiconductor foundries to complete the physical design. The physical layouts of cells in this library have the same height to simplify the placement problem and the power distribution network. Although the standard cell methodology also works for asynchronous designs, the performance is inferior compared with counterparts designed using the full-custom design methodology. To tackle this challenge, we propose a gridded cell layout methodology for asynchronous circuits, in which the cell height and cell width can be any integer multiple of two grid values. The gridded cell approach combines the shape regularity of standard cells with the size flexibility of full-custom layouts. Therefore, this approach can achieve a better space utilization ratio and lower wire length for asynchronous designs. Experiments have shown that the gridded cell placement approach reduces area without impacting the routability. We have also used this placer to tape out a chip in a 65nm process technology, demonstrating that our placer generates design-rule clean results

Advances in Energy System Optimization

The papers presented in this open access book address diverse challenges in decarbonizing energy systems, ranging from operational to investment planning problems, from market economics to technical and environmental considerations, from distribution grids to transmission grids, and from theoretical considerations to data provision concerns and applied case studies. While most papers have a clear methodological focus, they address policy-relevant questions at the same time. The target audience therefore includes academics and experts in industry as well as policy makers, who are interested in state-of-the-art quantitative modelling of policy relevant problems in energy systems. The 2nd International Symposium on Energy System Optimization (ISESO 2018) was held at the Karlsruhe Institute of Technology (KIT) under the symposium theme “Bridging the Gap Between Mathematical Modelling and Policy Support” on October 10th and 11th 2018. ISESO 2018 was organized by the KIT, the Heidelberg Institute for Theoretical Studies (HITS), the Heidelberg University, the German Aerospace Center and the University of Stuttgart