Review of System Design Frameworks

In the last decade, the enormous development of the semiconductor industry with ever-increasing complexities of digital embedded systems and strong market competition with fast time-to-market and low design cost demands have imposed serious difficulty to a conventional design method. Therefore, there emerges a new design flow named model-based system design, which is based on high-level abstraction models, heavy design automation, and extensive component reuse to increase productivity and satisfy the market pressure. This thesis presents reviews of ten high level academic system design frameworks and tools that have been proposed and implemented recently to support the model based design flow, namely System-on-Chip Environment (SCE), Embedded System Environment (ESE), Metropolis, Daedalus, SystemCoDesigner (SCD), xPilot, GAUT, No-Instruction-Set Computer (NISC), Formal System Design (ForSyDe), and Ptolemy II. These tools are then compared to each other in various aspects comprising objective, technique, implementation and capability. Following that, three design flow frameworks, including ESE, Daedalus, and SystemCoDesigner, are experimented for their real usage, performance and practicality. The frameworks and tools implementing the model-based design flow all show promising results. Modelling tools (ForSyDe, and Ptolemy II) can sufficiently capture a wide range of complicated modern systems, while high-level synthesis tools (xPilot, GAUT, and NISC) produce better design qualities in terms of area, power, and cost in comparison to traditional works. Study cases of design flow frameworks (SCE, ESE, Metropolis, Daedalus, and SCD) show the model-based method significantly reduces developing time as well as facilitates the system design process. However, most of these tools and frameworks are being incomplete, and still under the experimental stage. There still be a lot of works needed until the method can be put into practice

The Fifth NASA Symposium on VLSI Design

The fifth annual NASA Symposium on VLSI Design had 13 sessions including Radiation Effects, Architectures, Mixed Signal, Design Techniques, Fault Testing, Synthesis, Signal Processing, and other Featured Presentations. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The presentations share insights into next generation advances that will serve as a basis for future VLSI design

Transformation von Multiphysics-Modellen in einen FPGA-Entwurf für den echtzeitfähigen HiL-Test eingebetteter Systeme

Mit der vorliegenden Arbeit wird eine durchgängige Werkzeugkette von der Modellbildung physikalischer Simulationen bis zur Entwurfsautomatisierung für FPGA-basierte Echtzeitsimulationen etabliert. Modelica wurde als vielseitige, intuitive und objektorientierte Sprache zur Modellbildung ausgewählt. Die entwickelte Werkzeugkette nutzt Methoden der High-Level-Synthese, um einen Entwurf in VHDL zu generieren. Dabei können sowohl Entwürfe in Fließkomma-, als auch Festkomma-Arithmetik erzeugt werden

FPGA-friendly code compression for horizontal microcoded custom IPs

Shrinking time-to-market and high demand for productivity has driven traditional hardware designers to use design methodologies that start from high-level languages. However, meeting timing constraints of automatically generated IPs is often a challenging and time-consuming task that must be repeated every time the specification is modified. To address this issue, a new generation of IP-design technologies that is capable of generating custom datapaths as well as programming an existing one is developed. These technologies are often based on Horizontal Microcoded Architectures. Large code size is a well-know problem in HMAs, and is referred to as “code bloating ” problem. In this paper, we study the code size of one of the new HMA-based technologies called NISC. We show that NISC code size can be several times larger than a typical RISC processor, and we propose several low-overhead dictionary-based code compression techniques to reduce the code size. Our compression algorithm leverages the knowledge of “don’t care ” values in the control words to better compress the content of dictionary memories. Our experiments show that by selecting proper memory architectures the code size of NISC can be reduced by 70 % (i.e. 3.3 times) at cost of only 9% performance degradation. We also show that some code compression techniques may increase number of utilized block RAMs in FPGA-based implementations. To address this issue, we propose combining dictionaries and implementing them using embedded dual-port memories

FPGA-friendly Code Compression for Horizontal Microcoded Custom IPs

Shrinking time-to-market and high demand for productivity has driven traditional hardware designers to use design methodologies that start from high-level languages. However, meeting timing constraints of automatically generated IPs is often a challenging and time-consuming task that must be repeated every time the specification is modified. To address this issue, a new generation of IP-design technologies that is capable of generating custom datapaths as well as programming an existing one is developed. These technologies are often based on Horizontal Microcoded Architectures. Large code size is a well-know problem in HMAs, and is referred to as “code bloating ” problem. In this paper, we study the code size of one of the new HMAbased technologies called NISC. We show that NISC code size can be several times larger than a typical RISC processor, and we propose several low-overhead dictionary-based code compression techniques to reduce the code size. Our compression algorithm leverages the knowledge of “don’t care ” values in the control words to better compress the content of dictionary memories. Our experiments show that by selecting proper memory architectures the code size of NISC can be reduced by 70 % (i.e. 3.3 times) at cost of only 9% performance degradation. We also show that some code compression techniques may increase number of utilized block RAMs in FPGA-based implementations. To address this issue, we propose combining dictionaries and implementing them using embedded dual-port memories