Development Cost and Size Estimation Starting from High-Level Specifications

This paper addresses the problem of estimating cost and development effort of a system, starting from its complete or partial high-level description. In addition, some modifications to evaluate the cost-effectiveness of reusing VHDL-based designs, are presented. The proposed approach has been formalized using an approach similar to the COCOMO analysis strategy, enhanced by a project size prediction methodology based on a VHDL function point metric. The proposed design size estimation methodology has been validated through a significant benchmark, the LEON-1 microprocessor, whose VHDL description is of public domain

Dynamic HW/SW Partitioning: Configuration Scheduling and Design Space Exploration

Hardware/software partitioning is a process that occurs frequently in embedded system design. It is the procedure of determining whether a part of a system should be implemented in software or hardware. This dissertation is a study of hardware/software partitioning and the use of scheduling algorithms to improve the performance of dynamically reconfigurable computing devices. Reconfigurable computing devices are devices that are adaptable at the logic level to solve specific problems [Tes05]. One example of a reconfigurable computing device is the field programmable gate array (FPGA). The emergence of dynamically reconfigurable FPGAs made it possible to configure FPGAs at runtime. Most current approaches use a simple on demand configuration scheduling algorithm for the FPGA configurations. The on demand configuration scheduling algorithm reconfigures the FPGA at runtime, whenever a configuration is needed and is found not to be configured. The problem with this approach of dynamic reconfiguration is the reconfiguration time overhead, which is the time it takes to reconfigure the FPGA with a new configuration at runtime. Configuration caches and partial configuration have been proposed as possible solutions to this problem, but these techniques suffer from various limitations. The emergence of dynamically reconfigurable FPGAs also made it possible to perform dynamic hardware/software partitioning (DHSP), which is the procedure of determining at runtime whether a computation should be performed using its software or hardware implementation. The drawback of performing DHSP using configurations that are generated at runtime is that the profiling and the dynamic generation of configurations require profiling tool and synthesis tool access at runtime. This study proposes that configuration scheduling algorithms, which perform DHSP using statically generated configurations, can be developed to combine the advantages and reduce the major disadvantages of current approaches. A case study is used to compare and evaluate the tradeoffs between the currently existing approach for dynamic reconfiguration and the DHSP configuration scheduling algorithm based approach proposed in the study. A simulation model is developed to examine the performance of the various configuration scheduling algorithms. First, the difference in the execution time between the different approaches is analyzed. Afterwards, other important design criteria such as power consumption, energy consumption, area requirements and unit cost are analyzed and estimated. Also, business and marketing considerations such as time to market and development cost are considered. The study illustrates how different types of DHSP configuration scheduling algorithms can be implemented and how their performance can be evaluated using a variety of software applications. It is also shown how to evaluate when which of the approaches would be more advantageous by determining the tradeoffs that exist between them. Also the underlying factors that affect when which design alternative is more advantageous are determined and analyzed. The study shows that configuration scheduling algorithms, which perform DHSP using statically generated configurations, can be developed to combine the advantages and reduce some major disadvantages of current approaches. It is shown that there are situations where DHSP configuration scheduling algorithms can be more advantageous than the other approaches