Instruction Set Extension of a Low-End Reconfigurable Microcontroller in Bit-Sorting Implementation

The microcontroller-based system is currently having a tremendous boost with the revelation of platforms such as the Internet of Things. Low-end families of microcontroller architecture are still in demand albeit less technologically advanced due to its better I/O better application and control. However, there is clearly a lack of computational capability of the low-end architecture that will affect the pre-processing stage of the received data. The purpose of this research is to combine the best feature of an 8-bit microcontroller architecture together with the computationally complex operations without incurring extra resources. The modules’ integration is implemented using instruction set architecture (ISA) extension technique and is developed on the Field Programmable Gate Array (FPGA). Extensive simulations were performed with the and a comprehensive methodology is proposed. It was found that the ISA extension from 12-bit to 16-bit has produced a faster execution time with fewer resource utilization when implementing the bit-sorting algorithm. The overall development process used in this research is flexible enough for further investigation either by extending its module to more complex algorithms or evaluating other designs of its components

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

Using Rapid Prototyping in Computer Architecture Design Laboratories

This paper describes the undergraduate computer architecture courses and laboratories introduced at Georgia Tech during the past two years. A core sequence of six required courses for computer engineering students has been developed. In this paper, emphasis is placed upon the new core laboratories which utilize commercial CAD tools, FPGAs, hardware emulators, and a VHDL based rapid prototyping approach to simulate, synthesize, and implement prototype computer hardware

07361 Abstracts Collection -- Programming Models for Ubiquitous Parallelism

From 02.09. to 07.09.2007, the Dagstuhl Seminar 07361 ``Programming Models for Ubiquitous Parallelism\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

High speed simulation of microprocessor systems using LTU dynamic binary translation

This thesis presents new simulation techniques designed to speed up the simulation of microprocessor systems. The advanced simulation techniques may be applied to the simulator class which employs dynamic binary translation as its underlying technology. This research supports the hypothesis that faster simulation speeds can be realized by translating larger sections of the target program at runtime. The primary motivation for this research was to help facilitate comprehensive design-space exploration and hardware/software co-design of novel processor architectures by reducing the time required to run simulations. Instruction set simulators are used to design and to verify new system architectures, and to develop software in parallel with hardware. However, compromises must often be made when performing these tasks due to time constraints. This is particularly true in the embedded systems domain where there is a short time-to-market. The processing demands placed on simulation platforms are exacerbated further by the need to simulate the increasingly complex, multi-core processors of tomorrow. High speed simulators are therefore essential to reducing the time required to design and test advanced microprocessors, enabling new systems to be released ahead of the competition. Dynamic binary translation based simulators typically translate small sections of the target program at runtime. This research considers the translation of larger units of code in order to increase simulation speed. The new simulation techniques identify large sections of program code suitable for translation after analyzing a profile of the target program’s execution path built-up during simulation. The average instruction level simulation speed for the EEMBC benchmark suite is shown to be at least 63% faster for the new simulation techniques than for basic block dynamic binary translation based simulation and 14.8 times faster than interpretive simulation. The average cycle-approximate simulation speed is shown to be at least 32% faster for the new simulation techniques than for basic block dynamic binary translation based simulation and 8.37 times faster than cycle-accurate interpretive simulation

SIMULATION PLATFORM IN TLM OF SYSTEM ON CHIP USING RETARGETABLE ISS

System-on-Chip  (SoC) designs are increasingly becoming more complex. One of the major constraints is the time to market New design methods are necessary, and the tendency is with the integration of the software and hardware parts on the same chip.  Efficient on-chip communication architectures are critical for achieving desired performance in these systems  Thus, the development of codesign’s modern methods and  the appearance of hardware description languages  (HDL) based on C/C++ such as SystemC or specC allowing to employ the same language to describe the software and the hardware, and returning of this fact easier and more effective Co-simulation. These methods would be able to generate an optimal solution starting from a functional specification by reducing the time and the cost of the design. Thus, one of the main objectives of this paper is the development  of  a SystemC  platform  for multiprocessors architectural exploration at  the compromise  level  (TLM) by using SystemC/TLM.  It must  lead  to partition  system  into hw/sw and also  to validate  it by simulation or  to move easily modules from hardware to software (or vice versa) during the architectural exploration. Except for the software task priorities that could be modified, we only need to recompile and simulate 

Portable compiler optimisation across embedded programs and microarchitectures using machine learning

Building an optimising compiler is a difficult and time consuming task which must be repeated for each generation of a microprocessor. As the underlying microarchitecture changes from one generation to the next, the compiler must be retuned to optimise specifically for that new system. It may take several releases of the compiler to effectively exploit a processor’s performance potential, by which time a new generation has appeared and the process starts again. We address this challenge by developing a portable optimising compiler. Our approach employs machine learning to automatically learn the best optimisations to apply for any new program on a new microarchitectural configuration. It achieves this by learning a model off-line which maps a microarchitecture description plus the hardware counters from a single run of the program to the best compiler optimisation passes. Our compiler gains 67 % of the maximum speedup obtainable by an iterative compiler search using 1000 evaluations. We obtain, on average, a 1.16x speedup over the highest default optimisation level across an entire microarchitecture configuration space, achieving a 4.3x speedup in the best case. We demonstrate the robustness of this technique by applying it to an extended microarchitectural space where we achieve comparable performance