Packing LUT clusters with network flow programming

This paper describes a two-step packing algorithm for LUT clusters of which the LUT input multipliers are depopulated. In the first step, a greedy algorithm is used to search for BLE locations and cluster inputs. If the greedy algorithm fails, the second step with network flow programming algorithm is employed. Numerical results illustrate that our two-step packing algorithm obtains better packing density than one-step greedy packing algorithm.

Design and Verification of the Programming Circuit in an Application-Specific FPGA

In this paper we present a methodology and its implementation for the design and verification of programming circuit used in a family of application-specific FPGAs that share a common architecture. Each member of the family is different either in the types of functional blocks contained or in the number of blocks of each type. The parametrized design methodology is presented here to achieve this goal. Even though our focus is on the programming circuitry that provides the interface between the FPGA core circuit and the external programming hardware, the parametrized design method can be generalized to the design of entire chip for all members in the FPGA family. The method presented here covers the generation of the design RTL files and the support files for synthesis, place-and-route layout and simulations. The proposed method is proven to work smoothly within the complete chip design methodology. We will describe the implementation of this method to the design of the programming circuit in details including the design flow from the behavioral-level design to the final layout as well as the verification. Different package options and different programming modes are included in the description of the design. The circuit design implementation is based on SMIC 0.13-micron CMOS technology.

yet another meta-language for programming language processing

The formal specification language LFC was designed to support formal specification acquisition. However, it is yet suited to be used as a meta-language for specifying programming language processing. This paper introduces LFC as a meta-language, and compares it with ASF+SDF, an algebraic specification formalism that can also be used to programming languages.

extending the boundary of spreadsheet programming: lessons learned from chinese governmental projects

ICSE

A QUASI-SIMPLEX METHOD FOR STRICTLY CONVEX QUADRATIC PROGRAMMING

本文提出一个不用 Kuhn- Tucker条件而直接搜索严格凸二次规划最优目标点的鲁棒方法 .在搜索过程中 ,目标点沿约束多面体边界上的一条折线移动 .这种移动目标点的思想可以被认为是线性规划单纯形法的自然推广 ,在单纯形法中 ,目标点从一个顶点移到另一个顶点。

相同知识背景下技能之间迁移机制的研究

Since the middle of 1980's, the mechanisms of transfer of training between cognitive subskills rest on the same body of declarative knowledge has been highly concerned. The dominant theory is theory of common element (Singley & Anderson, 1989) which predict that there will be little or no transfer between subskills within the same domain when knowledge is used in different ways, even though the subskills might rest on a common body of declarative knowledge. This idea is termed as "principle of use specificity of knowledge" (Anderson, 1987). Although this principle has gained some empirical evidence from different domains such as elementary geometry (Neves & Anderson, 1981) and computer programming (McKendree & Anderson, 1987), it is challenged by some research (Pennington et al., 1991; 1995) in which substantially larger amounts of transfer of training was found between substills that rest on a shared declarative knowledge but share little procedures (production rules). Pennington et al. (1995) provided evidence that this larger amounts of transfer are due to the elaboration of declarative knowledge. Our research provide a test of these two different explanation, by considering transfer between two subskills within the domain of elementary geometry and elementary algebra respectively, and the inference of learning method ("learning from examples" and "learning from declarative-text") and subject ability (high, middle, low) on the amounts of transfer. Within the domain of elementary geometry, the two subskills of generating proofs" (GP) and "explaining proofs" (EP) which are rest on the declarative knowledge of "theorems on the characters of parallelogram" share little procedures. Within the domain of elementary algebra, the two subskills of "calculation" (C) and "simplification" (S) which are rest on the declarative knowledge of "multiplication of radical" share some more procedures. The results demonstrate that: 1. Within the domain of elementary geometry, although little transfer was found between the two subskills of GP and EP within the total subjects, different results occurred when considering the factor of subject's ability. Within the high level subjects, significant positive transfer was found from EP to GP, while little transfer was found on the opposite direction (i. e. from GP to EP). Within the low level subjects, significant positive transfer was found from EP to GP, while significant negative transfer was found on the opposite direction. For the middle level subject, little transfer was found between the two subskills. 2. Within the domain of elementary algebra, significant positive transfer was found from S to C, while significant negative transfer was found on the opposite direction (i. e. from C to S), when considering the total subjects. The same pattern of transfer occurred within the middle level subjects and low level subject. Within the high level subjects, no transfer was found between the two subskills. 3. Within theses two domains, different learning methods yield little influence on transfer of training between subskills. Apparently, these results can not be attributed to either common procedures or elaboration of declarative knowledge. A kind of synthetic inspection is essential to construct a reasonable explanation of these results which should take into account the following three elements: (1) relations between the procedures of subskills; (2) elaboration of declarative knowledge; (3) elaboration of procedural knowledge. 排Excluding the factor of subject, transfer of training between subskills can be predicted and explained by analyzing the relations between the procedures of two subskills. However, when considering some certain subjects, the explanation of transfer of training between subskills must include subjects' elaboration of declarative knowledge and procedural knowledge, especially the influence of the elaboration on performing the other subskill. The fact that different learning methods yield little influence on transfer of training between subskills can be explained by the fact that these two methods did not effect the level of declarative knowledge. Protocol analysis provided evidence to support these hypothesis. From this research, we conclude that in order to expound the mechanisms of transfer of training between cognitive subskills rest on the same body of declarative knowledge, three elements must be considered synthetically which include: (1) relations between the procedures of subskills; (2) elaboration of declarative knowledge; (3) elaboration of procedural knowledge.