Uppsats

Software Synthesis of Synchronous Data Flow Models Using ForSyDe IO

Master-uppsats

KTH/Skolan för elektroteknik och datavetenskap (EECS)

Publicerad: 2022

Språk: Engelska

Sammanfattning

The implementation of embedded software applications is a complex process. The complexity arises from the intense time-to-market pressures; power and memory constraints. To deal with this complexity, an idea is to automatically construct the applications based on the high-level abstraction model. Synchronous data flow (SDF) is a high-level model of computation, and is used to model the embedded applications. Formal System Design (ForSyDe), developed by ForSyDe group at KTH Royal Institute of Technology, is a methodology for modeling and designing heterogeneous systems-on-chip. The aim of Formal System Design (ForSyDe) is to automatically generate the detailed software implementation or hardware implementation according to the high-level system specification. Formal System Design (ForSyDe) starts from the high-level system specification and specifies the system model in Haskell language. Synchronous data flow is supported by ForSyDe. ForSyDe IO is an intermediate representation of the high-level system specification. This master thesis focuses on the software synthesis of synchronous data flow models specified in ForSyDe IO, and aims to produce an automatic code generator that can generate software applications in C code for different platforms based on ForSyDe IO. In this project, a software synthesis method for ForSyDe IO was proposed. Then, based on the software synthesis method, a code generator, written in Java and Xtend, was designed. The derived code generator was tested on two examples. The experiment results show that the synchronous data flow models specified in ForSyDe IO are successfully synthesized into C code. The code is in the Github repository https://github.com/Rojods/CInTSyDe.git with MIT license.

Information

Författare
Zhao, Yihang
Lärosäte / institution
KTH/Skolan för elektroteknik och datavetenskap (EECS)
Publiceringsdatum
2022
Uppsatstyp
Master-uppsats
Språk
Engelska

Utforska vidare

Liknande uppsatser

Uppsatser med liknande ämnen och nyckelord.