As a design flow for low-power FPGA implementation, Datapath-Layout-Driven Design (DLDD) has been proposed. This letter reports the effect of DLDD for standard-cell-based ASIC implementation, and proposes necessary improvements. Experimental results shows that about 8.3% reduction of power dissipation is achieved in the best case.

Binary Decision Diagrams (BDDs) are graph representation of Boolean functions. In particular, Ordered BDDs (OBDDs) are useful in many situations, because they provide canonical representation and they are manipulated efficiently. BDD packages which automatically generate OBDDs have been developed, and they are now widely used in logic design area, including formal verification and logic synthesis. Synthesis of pass-transistor circuits is one of successful applications of such BDD packages. Pass-transistor circuits are generated from BDDs by mapping each node to a selector which consists of two or four pass transistors. If circuits are generated from smaller BDDs, generated circuits have smaller number of transistors and hence save chip area and power consumption. In this paper, more generic BDDs which have no restrictions in variable ordering and variable appearance count on its paths are called Generic BDDs (GBDDs), and an algorithm for generating GBDDs is proposed for the purpose of synthesis of pass-transistor circuits. The proposed algorithm consists of two steps. At the first step, parse trees (PTs) for given Boolean formulas are generated, where a PT is a directed tree representation of Boolean formula(s) and it consists of literal nodes and operation nodes. In this step, our algorithm attempts to reduce the number of literal nodes of PTs. At the second step, a GBDD is generated for the PTs using Concatenation Method, where Concatenation Method generates a GBDD by connecting GBDDs vertically. In this step, our algorithm attempts to share isomorphic subgraphs. In experiments on ISCAS'89 and MCNC benchmark circuits, our program successfully generated 32 GBDDs out of 680 single-output functions and 4 GBDDs out of 49 multi-output functions whose sizes are smaller than OBDDs. GBDD size is reduced by 23.1% in the best case compared with OBDD.

Floating-point units (FPUs) are indispensable in processors, 3D-graphic engines, etc. To improve design productivity of these LSIs, FPU IPs are strongly desired. However, it is impossible to cover wide range of needs by an FPU IP, because there are various kind of options in specifications (e.g., operating frequency, latency, and ability of pipeline operation) and implementations (e.g., hardware algorithms). Thus, multiple IPs are needed even for the same functionality. In this paper, we propose to build an IP Library which consists of large number of FPU IPs with various kind of specifications and implementations, and which has catalogue data that shows not only specifications but also post-layout area and power dissipation of each IP. As the first step of the project, we have developed an IP Library targeted to Rohm 0.35 µm triple-metal process, which consists of 20 IPs for IEEE-754-standard single-precision floating-point division with 5 operating frequencies (50 MHz, 75 MHz, 100 MHz, 125 MHz, and 150 MHz), with two options whether pipelined or not, and with two hardware algorithms (the restoring method and the SRT method). We have also developed a catalogue for the IP Library, which shows post-layout area and power dissipation as well as specification of each IP. We have introduced two metrics "performance-area ratio (MFLOPS/mm2)" and "performance-power ratio (MFLOPS/W)" to afford a good insight into efficiency of implementations. From the catalogue data, the restoring method is, on the average, 1.4 times and 2.3 times better than the SRT method in terms of performance-area ratio and performance-power ratio, respectively. The developed catalogue is usable not only for selection of the optimal IP for a specific application, but also for quantitative analysis at the early stage of architecture design. It is also expected that the catalogue data based on an actual process technology is valuable for education.

In high performance compilers to process pointer-handling programs, precise pointer alias analysis is useful for the compilers to generate efficient object code. It is well known that most compiler techniques such as data flow analysis, dependence analysis, side effect analysis and optimizations are related to the alias problem. However, without data structure information, there is a limit on the precision of the alias analysis. Even though the automatic data structure detection problem is complex, when pointer manipulation satisfies some restrictions, some data structures can be detected automatically by compilers with some knowledge of aliases. In this paper, we propose an automatic data structure detection method for Pascal and Fortran 90. Linear list, tree and dag data structures are detected. Detected data structure information can be used not only for raising the precision of alias analysis but also for some optimizing techniques for pointer handling programs directly.