Federal agricultural, conservation and food assistance programs are critical policies for the agricultural and food sectors. Historically, these policies have been reauthorized by the United States Congress every five years. Also known as the Farm Bill, it authorizes four major categories of mandatory spending programs, distributing benefits to those entitled to receive them. These four categories align with the following titles in the Farm Bill: Title I: Commodities; Title II: Conservation; Title XI: Crop Insurance; and the Supplemental Nutrition Assistance Program under Title IV: Nutrition. We present the Policy Design Lab, a comprehensive web platform for data visualization and analysis of policy data. The core goal is to better inform policymakers, the public and other stakeholders to improve policy understanding, as well as to provide comparative analysis of policy design alternatives and innovations. It provides a powerful tool for designing, considering and evaluating different scenarios by visualizing data and modeling the likely outcomes of the various designs. We describe the main modules of this web platform, the design and development process, and the integration of two models that support policy analysis and design.

The relentless proliferation of Big Data and artificial intelligence has compelled computing platform architectures to evolve into heterogeneous multicores for greater energy efficiency. A customized network-on-chip (NoC) supporting interconnection diversity is pivotal for the asymmetric data-access traffic requirements of modern heterogeneous multicore system-on-chip (SoC). A significant portion of on-chip data access comprises single-source multi-destination (SSMD) traffic, which supports barrier synchronization, multi-threading, cache coherency protocols, and deep neural network (DNN) acceleration. By amortizing SSMD traffic, multicast routing is essential for effectively utilizing communication bandwidth. One of the primary concerns in supporting multicast routing in NoCs is to circumvent the additional deadlock conditions caused by branch operations among the active routers. However, it is challenging to implement the throughput-optimized multicast routing in irregular topology-based NoCs because the deadlock conditions become highly complicated, and the Hamiltonian path required to apply the labeling rule may not exist. Two important observations were identified regarding multicast routing in customized NoCs: 1) Even if the NoC lacks a Hamiltonian path, deadlock-freedom can be guaranteed by restricting branch operations to a specific destination. 2) A variable path diversity in a custom topology can be leveraged in routing path allocation and branch. Based on these properties, this study proposes a deadlock-free and throughput-enhanced multicast routing for customized NoC (MRCN). MRCN ensures deadlock freedom by utilizing extended routing and router labeling rules. Furthermore, destination router partitioning and traffic-aware adaptive branching are incorporated to reduce packet routing hops and disperse channel traffic. The effectiveness of MRCN was verified using Noxim, a well-known cycle-accurate NoC simulator, under various topologies and traffic patterns. The simulation revealed that MRCN improved the average latency by 13.98 % and the throughput by 12.16 % under the saturated traffic conditions over the previous multicast routings in customized NoCs.

State-of-the-art silicon photonics technology has demonstrated its potential use in all required building blocks for ultrahigh bandwidth on-chip optical links. However, a robust system-level abstraction model reflecting the properties of optical devices has not been well established. We propose a linear optical device model (LODM) for silicon photonic devices and an associated computation method of optical signal propagation (CMOP) in an optical network-on-chip (ONoC). The CMOP manipulates the optical signal routing paths according to the topology, router configuration, and routing algorithm of the given ONoC architecture; thus, it allows the transformed information to be adaptable in an LODM to facilitate simplified analysis. Furthermore, we construct a linear system model of a microring resonator (MR) to reduce the computation complexities caused by its resonance structure. By using the CMOP, we accelerate the system-level analysis of optical signal propagation in ONoCs, reflecting the propagation loss, interference, and phase shift with close accuracy to analog and mixed-signal extensions (AMS) environments. The evaluation results show that the computation speeds up by three orders of magnitude with 1.57% error in accuracy when compared to the AMS environments.

Abstract Summary: BioSilico is a web-based database system that facilitates the search and analysis of metabolic pathways. Heterogeneous metabolic databases including LIGAND, ENZYME, EcoCyc and MetaCyc are integrated in a systematic way, thereby allowing users to efficiently retrieve the relevant information on enzymes, biochemical compounds and reactions. In addition, it provides well-designed view pages for more detailed summary information. BioSilico is developed as an extensible system with a robust systematic architecture. Availability: BioSilico database system is accessible at http://biosilico.kaist.ac.kr