Methodology for standard cell compliance and detailed placement for triple patterning lithography

As the feature size of semiconductor process further scales to sub-16nm technology node, triple patterning lithography (TPL) has been regarded one of the most promising lithography candidates. M1 and contact layers, which are usually deployed within standard cells, are most critical and complex parts for modern digital designs. Traditional design flow that ignores TPL in early stages may limit the potential to resolve all the TPL conflicts. In this paper, we propose a coherent framework, including standard cell compliance and detailed placement to enable TPL friendly design. Considering TPL constraints during early design stages, such as standard cell compliance, improves the layout decomposability. With the pre-coloring solutions of standard cells, we present a TPL aware detailed placement, where the layout decomposition and placement can be resolved simultaneously. Our experimental results show that, with negligible impact on critical path delay, our framework can resolve the conflicts much more easily, compared with the traditional physical design flow and followed layout decomposition

An angle-based interest model for text recommendation

Building an interest model is the key to realize personalized text recommendation. Previous interest models neglect the fact that a user may have multiple angles of interests. Different angles of interest provide different requests and criteria for text recommendation. This paper proposes an interest model that consists of two kinds of angles: persistence and pattern, which can be combined to form complex angles. The model uses a new method to represent the long-term interest and the short-term interest, and distinguishes the interest on object and the interest on the link structure of objects. Experiments with news-scale text data show that the interest on object and the interest on link structure have real requirements, and it is effective to recommend texts according to the angles

An Ant Colony-based Heuristic Algorithm for Joint Scheduling of Post-earthquake Road Repair and Relief Distribution

Emergency road repair and distribution of relief goods are crucial for post-earthquake response. However, interrelationships between those two tasks are not adequately considered in their work schedules, especially in cases with very limited repair resources, leading to unnecessary delay and expenditure. A time-space network model is constructed to better describe the constraints arising from the interrelationships in joint scheduling of road repair and relief distribution works. An ant colony-based heuristic algorithm is developed to solve the NP-hard model efficiently for practical use, followed by a case study of Wenchuan earthquake to validate the planning tool and to demonstrate its feasibility for resolving real world problem

ShenZhen transportation system (SZTS): a novel big data benchmark suite

Data analytics is at the core of the supply chain for both products and services in modern economies and societies. Big data workloads, however, are placing unprecedented demands on computing technologies, calling for a deep understanding and characterization of these emerging workloads. In this paper, we propose ShenZhen Transportation System (SZTS), a novel big data Hadoop benchmark suite comprised of real-life transportation analysis applications with real-life input data sets from Shenzhen in China. SZTS uniquely focuses on a specific and real-life application domain whereas other existing Hadoop benchmark suites, such as HiBench and CloudRank-D, consist of generic algorithms with synthetic inputs. We perform a cross-layer workload characterization at the microarchitecture level, the operating system (OS) level, and the job level, revealing unique characteristics of SZTS compared to existing Hadoop benchmarks as well as general-purpose multi-core PARSEC benchmarks. We also study the sensitivity of workload behavior with respect to input data size, and we propose a methodology for identifying representative input data sets

Bis[4-(2-aza­niumyleth­yl)piperazin-1-ium] di-μ-sulfido-bis­[disulfido­germanate(II)]

In the title compound, (C6H17N3)2[Ge2S6], the dimeric [Ge2S6]4− anion is formed by two edge-sharing GeS4 tetra­hedral units. The average terminal and bridging Ge—S bond lengths are 2.164 (2) and 2.272 (8) Å, respectively. The dimeric inorganic anions and the organic piperazinium cations are organized into a three-dimensional network by N—H⋯S hydrogen bonds