4,267 research outputs found
Coarse-grained reconfigurable array architectures
Coarse-Grained Reconfigurable Array (CGRA) architectures accelerate the same inner loops that benefit from the high ILP support in VLIW architectures. By executing non-loop code on other cores, however, CGRAs can focus on such loops to execute them more efficiently. This chapter discusses the basic principles of CGRAs, and the wide range of design options available to a CGRA designer, covering a large number of existing CGRA designs. The impact of different options on flexibility, performance, and power-efficiency is discussed, as well as the need for compiler support. The ADRES CGRA design template is studied in more detail as a use case to illustrate the need for design space exploration, for compiler support and for the manual fine-tuning of source code
A Comparative Study of Scheduling Techniques for Multimedia Applications on SIMD Pipelines
Parallel architectures are essential in order to take advantage of the
parallelism inherent in streaming applications. One particular branch of these
employ hardware SIMD pipelines. In this paper, we analyse several scheduling
techniques, namely ad hoc overlapped execution, modulo scheduling and modulo
scheduling with unrolling, all of which aim to efficiently utilize the special
architecture design. Our investigation focuses on improving throughput while
analysing other metrics that are important for streaming applications, such as
register pressure, buffer sizes and code size. Through experiments conducted on
several media benchmarks, we present and discuss trade-offs involved when
selecting any one of these scheduling techniques.Comment: Presented at DATE Friday Workshop on Heterogeneous Architectures and
Design Methods for Embedded Image Systems (HIS 2015) (arXiv:1502.07241
Runtime Scheduling, Allocation, and Execution of Real-Time Hardware Tasks onto Xilinx FPGAs Subject to Fault Occurrence
This paper describes a novel way to exploit the computation capabilities delivered by modern Field-Programmable Gate Arrays (FPGAs), not only towards a higher performance, but also towards an improved reliability. Computation-specific pieces of circuitry are dynamically scheduled and allocated to different resources on the chip based on a set of novel algorithms which are described in detail in this article. These algorithms consider most of the technological constraints existing in modern partially reconfigurable FPGAs as well as spontaneously occurring faults and emerging permanent damage in the silicon substrate of the chip. In addition, the algorithms target other important aspects such as communications and synchronization among the different computations that are carried out, either concurrently or at different times. The effectiveness of the proposed algorithms is tested by means of a wide range of synthetic simulations, and, notably, a proof-of-concept implementation of them using real FPGA hardware is outlined
Towards Python-based Domain-specific Languages for Self-reconfigurable Modular Robotics Research
This paper explores the role of operating system and high-level languages in
the development of software and domain-specific languages (DSLs) for
self-reconfigurable robotics. We review some of the current trends in
self-reconfigurable robotics and describe the development of a software system
for ATRON II which utilizes Linux and Python to significantly improve software
abstraction and portability while providing some basic features which could
prove useful when using Python, either stand-alone or via a DSL, on a
self-reconfigurable robot system. These features include transparent socket
communication, module identification, easy software transfer and reliable
module-to-module communication. The end result is a software platform for
modular robots that where appropriate builds on existing work in operating
systems, virtual machines, middleware and high-level languages.Comment: Presented at DSLRob 2011 (arXiv:1212.3308
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