Application specific instruction set processor design for embedded application using the coware tool

An Application Specific Instruction Set Processor (ASIP) is widely used as a System on a Chip(SoC) Component. ASIPs possess an instruction set which is tai-lored to benefit a specific application. Such specialization allows ASIPs to serve as an intermediate between two dominant processor design styles- ASICs which has high processing abilities at the cost of limited programmability and Programmable solu-tions such as FPGAs that provide programming exibility at the cost of less energy eficiency. In this dissertation the goal is to design ASIP, keeping in mind a temper-ature sensor system. The platform used for processor design is LISA 2.0 description language and processor designing environment from CoWare. Coware processor de-signer allows processor architecture to be defined at an abstract level and automatic generation of chain of software tools like assembler, linker and simulator for functional verification followed by RTL level description. RTL level description is used to gen-erate synthesized report of the design using RTL compiler and finally the layout is created using Cadence encounter

KAVUAKA: a low-power application-specific processor architecture for digital hearing aids

The power consumption of digital hearing aids is very restricted due to their small physical size and the available hardware resources for signal processing are limited. However, there is a demand for more processing performance to make future hearing aids more useful and smarter. Future hearing aids should be able to detect, localize, and recognize target speakers in complex acoustic environments to further improve the speech intelligibility of the individual hearing aid user. Computationally intensive algorithms are required for this task. To maintain acceptable battery life, the hearing aid processing architecture must be highly optimized for extremely low-power consumption and high processing performance.The integration of application-specific instruction-set processors (ASIPs) into hearing aids enables a wide range of architectural customizations to meet the stringent power consumption and performance requirements. In this thesis, the application-specific hearing aid processor KAVUAKA is presented, which is customized and optimized with state-of-the-art hearing aid algorithms such as speaker localization, noise reduction, beamforming algorithms, and speech recognition. Specialized and application-specific instructions are designed and added to the baseline instruction set architecture (ISA). Among the major contributions are a multiply-accumulate (MAC) unit for real- and complex-valued numbers, architectures for power reduction during register accesses, co-processors and a low-latency audio interface. With the proposed MAC architecture, the KAVUAKA processor requires 16 % less cycles for the computation of a 128-point fast Fourier transform (FFT) compared to related programmable digital signal processors. The power consumption during register file accesses is decreased by 6 %to 17 % with isolation and by-pass techniques. The hardware-induced audio latency is 34 %lower compared to related audio interfaces for frame size of 64 samples.The final hearing aid system-on-chip (SoC) with four KAVUAKA processor cores and ten co-processors is integrated as an application-specific integrated circuit (ASIC) using a 40 nm low-power technology. The die size is 3.6 mm2. Each of the processors and co-processors contains individual customizations and hardware features with a varying datapath width between 24-bit to 64-bit. The core area of the 64-bit processor configuration is 0.134 mm2. The processors are organized in two clusters that share memory, an audio interface, co-processors and serial interfaces. The average power consumption at a clock speed of 10 MHz is 2.4 mW for SoC and 0.6 mW for the 64-bit processor.Case studies with four reference hearing aid algorithms are used to present and evaluate the proposed hardware architectures and optimizations. The program code for each processor and co-processor is generated and optimized with evolutionary algorithms for operation merging,instruction scheduling and register allocation. The KAVUAKA processor architecture is com-pared to related processor architectures in terms of processing performance, average power consumption, and silicon area requirements

Design of an Application Specific Instruction Set Processor Using LISA

A Digital Signal Processor with specific instruction sets and meant for a specific application is called as Application Specific Instruction set Processor(ASIP). To design an ASIP many approaches are available. However optimization of an ASIP becomes handy if it is designed in a higher level of abstraction that is higher than Register Transfer Level (RTL). Application Description Languages (ADLs) are becoming popular recently because of its quick and optimal design convergence achievement capability during the design of ASIPs. Several stages are required to design a processor which are architecture design implementation, software development, instruction and system verification. Verification of such ASIPs at various design stages is a tedious job to do. This thesis presents the architecture description of a simple DSP processor using ADL based instruction set description. The design process is more consistent after allowing maximum flexibility here. Further more, it enables the design process in both instruction and cycle accurate modes. The design process of a three stage pipelined FIR Filter processor is demonstrated as a case study. Further optimization can be done with respect to resources, memory size and power consumption by changing the LISA code written in CoWare platform

Back-annotation for interactive data path synthesis

In order to take into account physical design effects, a designer needs a feedback mechanism during interactive data path synthesis. In this paper, we propose a hypergraph model and a back-annotation algorithm which provide a feedback mechanism for back-annotation from physical designs to behavioral descriptions. Given a control data flow graph and its structural design, this back-annotation technique cannot only evaluate the design quality but can also feedback the delay to each edge and node in the graph. Therefore, a designer can identify the critical paths and improve the design. The hypergraph model and the back-annotation algorithm allow us to bridge the gap between the behavioral description and the physical design

Embedded DSP Processor Design using Coware Processor Designer and Magma Layout Tool

A Digital Signal Processing (DSP) application can be implemented in a variety of ways. The objective of this project is to design an Embedded DSP Processor. The desired processor is run by an instruction set. Such a processor is called an Application Specific Instruction Set Processor (ASIP). ASIP is becoming essential to convergent System on Chip (SoC) Design. Usually there are two approaches to design an ASIP. One of them is at Register Transfer Level (RTL) and another is at just higher level than RTL and is known as Electronic System Level (ESL). Application Description Languages (ADLs) are becoming popular recently because of its quick and optimal design convergence achievement capability during the design of ASIPs. In this project we first concentrate on the implementation and optimization of an ASIP using an ADL known as Language for Instruction Set Architecture (LISA) and CoWare Processor Designer environment. We have written a LISA 2.0 description of the processor. Given a LISA code, the CoWare Processor Designer (PD) then generates Software Development tools like assembler, disassembler, linker and compiler. A particular application in assembly language to find out the convolution using FIR filter is then run on the processor. Provided that the functionality of the processor is correct, synthesizable RTL for the processor can be generated using Coware Processor Generator. Using the RTL generated, we implemented our processor in the following IC Design technologies: • Semi-Custom IC Design Technology Here, the RTL is synthesized using Magma Blast Create Tool and the final Layout is drawn using Magma Blast Fusion Tool • Programmable Logic Device IC Design Technology Here, the processor is dumped to a Field Programmable Gate Array (FPGA). The FPGA used for this purpose is Xilinx Virtex II Pro

Silicon compilation

Silicon compilation is a term used for many different purposes. In this paper we define silicon compilation as a mapping from some higher level description into layout. We define the basic issues in structural and behavioral silicon compilation and some possible solutions to those issues. Finally, we define the concept of an intelligent silicon compiler in which the compiler evaluates the quality of the generated design and attempts to improve it if it is not satisfactory

Low Power SoC Design

The design of Low Power Systems-on-Chips (SoC) in very deep submicron technologies becomes a very complex task that has to bridge very high level system description with low-level considerations due to technology defaults and variations and increasing system and circuit complexity. This paper describes the major low-level issues, such as dynamic and static power consumption, temperature, technology variations, interconnect, DFM, reliability and yield, and their impact on high-level design, such as the design of multi-Vdd, fault-tolerant, redundant or adaptive chip architectures. Some very low power System-on-Chip (SoC) will be presented in three domains: wireless sensor networks, vision sensors and mobile TV

Layout area models for high-level synthesis

Traditionally, the common cost functions, the number of functional units, registers and selector inputs, are used in high level synthesis as quality measures. However, these traditional design quality measures may not reflect the real physical design. To establish quality measures based on the physical designs, we propose layout estimation models for two commonly used data path and control layout architectures. The results show that quality measures deriving from our models give an accurate prediction of the final layout. The results also show that traditional cost functions are not good indicators for optimization in high level synthesis