Pipelined Data Path Synthesis Research Articles

Time-Constrained Scheduling and Module Allocation for On-Line Testability in Pipelined Data Paths

Abstract This paper presents an on-line testable-pipelined data path synthesis with the goal of minimizing testing time. An independent time-constrained scheduling with a module allocation algorithm for a pipelined data path is proposed. The algorithm takes any behavioral description represented as a data flow graph as input and generates a pipelined data path. The pipelined data path is composed of resources such as modules, registers, and multiplexers. Our on-line testing methodology applies to modules where multi type operations are assigned. The test is performed on each type of operation assigned to a module. The testing time is reduced by minimizing the overall number of types of operations assigned to modules. Thus, the objective is to minimize the overall number of types of operations assigned to all modules by performing pipelined data path synthesis. Experimental results confirm there can be some improvement in minimizing the overall number of types of operations assigned to all modules.

Design of a pipelined datapath synthesis system for digital signal processing

In this paper, we describe the design of SODAS-DSP (Sogang Design Automation System-DSP), a pipelined datapath synthesis system targeted for application-specific DSP chip design. Through facilitated user interaction, the design space of pipelined datapaths for given design descriptions can be explored to produce an optimal design which meets design constraints. Taking SFG (Signal Flow Graph) in schematic as inputs, SODAS-DSP generates pipelined datapaths through scheduling and module allocation processes. New scheduling and module allocation algorithms are proposed for efficient synthesis of pipelined hardwares. The proposed scheduling algorithm is of iterative/constructive nature, where the measure of equidistribution of operations among pipeline partitions is adopted as the objective function. Module allocation is performed in two passes: the first pass for initial allocation and the second one for seduction of interconnection cost. In the experiments, we compare the synthesis results for benchmark examples with those of recent pipelined datapath synthesis systems, Sehwa and PISYN, and show the effectiveness of SODAS-DSP.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Synthesis of pipelined data paths

The paper presents a scheduling algorithm for pipelined data-path synthesis. The algorithm is generic, in the sense that it can also be used for nonpipelined data paths. The algorithm takes as inputs a dataflow graph representing the behavioural specification of a design, a design library, the required throughput, and the area constraint. It first determines feasible sets of useable function units and their corresponding latencies. Operations on the critical paths are checked so that it can be seen whether they can be scheduled with the chosen function units and latency. In case of a failure, delay operators are inserted into the critical paths to redistribute the load. In the scheduling of the operations on the off-critical paths, the concurrency of operations is balanced. The algorithm is iterative, with one operation being scheduled in each iteration. In each iteration, an operation type is selected first by the use of a priority function. One of the operations that can be placed in the least dense partition (control steps) of the distribution graph of the selected operation type is then scheduled. A 16-point FIR filter is used to illustrate the scheduling algorithm.

Sehwa: a software package for synthesis of pipelines from behavioral specifications

A set of techniques for the synthesis of pipelined data paths is described, and Sehwa, a program that performs such synthesis, is presented. The task includes the generation of data paths from a data-flow graph along with a clocking scheme that overlaps execution of multiple tasks. Some design examples are given. Sehwa can find the minimum-cost design, the highest performance design, and other designs between these two in the design space. Sehwa is written in Franz Lisp and executes within minutes, for problems of practical size, on a VAX 11/750. >