3,115 research outputs found
Low Power Processor Architectures and Contemporary Techniques for Power Optimization ā A Review
The technological evolution has increased the number of transistors for a given die area significantly and increased the switching speed from few MHz to GHz range. Such inversely proportional decline in size and boost in performance consequently demands shrinking of supply voltage and effective power dissipation in chips with millions of transistors. This has triggered substantial amount of research in power reduction techniques into almost every aspect of the chip and particularly the processor cores contained in the chip. This paper presents an overview of techniques for achieving the power efficiency mainly at the processor core level but also visits related domains such as buses and memories. There are various processor parameters and features such as supply voltage, clock frequency, cache and pipelining which can be optimized to reduce the power consumption of the processor. This paper discusses various ways in which these parameters can be optimized. Also, emerging power efficient processor architectures are overviewed and research activities are discussed which should help reader identify how these factors in a processor contribute to power consumption. Some of these concepts have been already established whereas others are still active research areas. Ā© 2009 ACADEMY PUBLISHER
Coarse-grained reconfigurable array architectures
Coarse-Grained Reconļ¬gurable Array (CGRA) architectures accelerate the same inner loops that beneļ¬t 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 efļ¬ciently. 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 ļ¬exibility, performance, and power-efļ¬ciency 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 ļ¬ne-tuning of source code
Low-Power and Reconfigurable Asynchronous ASIC Design Implementing Recurrent Neural Networks
Artificial intelligence (AI) has experienced a tremendous surge in recent years, resulting in high demand for a wide array of implementations of algorithms in the field. With the rise of Internet-of-Things devices, the need for artificial intelligence algorithms implemented in hardware with tight design restrictions has become even more prevalent. In terms of low power and area, ASIC implementations have the best case. However, these implementations suffer from high non-recurring engineering costs, long time-to-market, and a complete lack of flexibility, which significantly hurts their appeal in an environment where time-to-market is so critical. The time-to-market gap can be shortened through the use of reconfigurable solutions, such as FPGAs, but these come with high cost per unit and significant power and area deficiencies over their ASIC counterparts. To bridge these gaps, this dissertation work develops two methodologies to improve the usability of ASIC implementations of neural networks in these applications.
The first method demonstrates a method for substantial reductions in design time for asynchronous implementations of a set of AI algorithms known as Recurrent Neural Networks (RNN) by analyzing the possible architectures and implementing a library of generic or easily altered components that can be used to quickly implement a chosen RNN architecture. A tapeout of this method was completed using as few as 112 hours of labor by the designer from RNN selection to a DRC/LVS clean chip layout ready for fabrication.
The second method develops a flow to implement a set of RNNs in a single reconfigurable ASIC, offering a middle ground between fully reconfigurable solutions and completely application-specific implementations. This reconfigurable design is capable of representing thousands of possible RNN configurations in a single IC. A tapeout of this design was also completed, with both tapeouts using the TSMC 65nm bulk CMOS process
Cross-Layer Rapid Prototyping and Synthesis of Application-Specific and Reconfigurable Many-accelerator Platforms
Technological advances of recent years laid the foundation consolidation of informatisationof society, impacting on economic, political, cultural and socialdimensions. At the peak of this realization, today, more and more everydaydevices are connected to the web, giving the term āInternet of Thingsā. The futureholds the full connection and interaction of IT and communications systemsto the natural world, delimiting the transition to natural cyber systems and offeringmeta-services in the physical world, such as personalized medical care, autonomoustransportation, smart energy cities etc. . Outlining the necessities of this dynamicallyevolving market, computer engineers are required to implement computingplatforms that incorporate both increased systemic complexity and also cover awide range of meta-characteristics, such as the cost and design time, reliabilityand reuse, which are prescribed by a conflicting set of functional, technical andconstruction constraints. This thesis aims to address these design challenges bydeveloping methodologies and hardware/software co-design tools that enable therapid implementation and efficient synthesis of architectural solutions, which specifyoperating meta-features required by the modern market. Specifically, this thesispresents a) methodologies to accelerate the design flow for both reconfigurableand application-specific architectures, b) coarse-grain heterogeneous architecturaltemplates for processing and communication acceleration and c) efficient multiobjectivesynthesis techniques both at high abstraction level of programming andphysical silicon level.Regarding to the acceleration of the design flow, the proposed methodologyemploys virtual platforms in order to hide architectural details and drastically reducesimulation time. An extension of this framework introduces the systemicco-simulation using reconfigurable acceleration platforms as co-emulation intermediateplatforms. Thus, the development cycle of a hardware/software productis accelerated by moving from a vertical serial flow to a circular interactive loop.Moreover the simulation capabilities are enriched with efficient detection and correctiontechniques of design errors, as well as control methods of performancemetrics of the system according to the desired specifications, during all phasesof the system development. In orthogonal correlation with the aforementionedmethodological framework, a new architectural template is proposed, aiming atbridging the gap between design complexity and technological productivity usingspecialized hardware accelerators in heterogeneous systems-on-chip and networkon-chip platforms. It is presented a novel co-design methodology for the hardwareaccelerators and their respective programming software, including the tasks allocationto the available resources of the system/network. The introduced frameworkprovides implementation techniques for the accelerators, using either conventionalprogramming flows with hardware description language or abstract programmingmodel flows, using techniques from high-level synthesis. In any case, it is providedthe option of systemic measures optimization, such as the processing speed,the throughput, the reliability, the power consumption and the design silicon area.Finally, on addressing the increased complexity in design tools of reconfigurablesystems, there are proposed novel multi-objective optimization evolutionary algo-rithms which exploit the modern multicore processors and the coarse-grain natureof multithreaded programming environments (e.g. OpenMP) in order to reduce theplacement time, while by simultaneously grouping the applications based on theirintrinsic characteristics, the effectively explore the design space effectively.The efficiency of the proposed architectural templates, design tools and methodologyflows is evaluated in relation to the existing edge solutions with applicationsfrom typical computing domains, such as digital signal processing, multimedia andarithmetic complexity, as well as from systemic heterogeneous environments, suchas a computer vision system for autonomous robotic space navigation and manyacceleratorsystems for HPC and workstations/datacenters. The results strengthenthe belief of the author, that this thesis provides competitive expertise to addresscomplex modern - and projected future - design challenges.ĪĪ¹ ĻĪµĻĪ½ĪæĪ»ĪæĪ³Ī¹ĪŗĪĻ ĪµĪ¾ĪµĪ»ĪÆĪ¾ĪµĪ¹Ļ ĻĻĪ½ ĻĪµĪ»ĪµĻ
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ĻĪ·ĻĪµĻĪÆĪµĻ ĻĻĪæĪ½ ĻĻ
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Ī¼Ī·ĻĪĻ ĻĻĪæĪ“Ī¹Ī±Ī³ĻĪ±ĻĪĻ, ĻĪµ ĻĪ»ĪµĻ ĻĪ¹Ļ ĻĪ¬ĻĪµĪ¹Ļ Ī±Ī½Ī¬ĻĻĻ
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ĻĻ
ĻĻĪ®Ī¼Ī±ĻĪæĻ. Ī£Īµ ĪæĻĪøĪæĪ³ĻĪ½Ī¹Ī± ĻĻ
Ī½Ī¬ĻĪµĪ¹Ī± Ī¼Īµ ĻĪæ ĻĻĪæĪ±Ī½Ī±ĻĪµĻĪøĪĪ½ Ī¼ĪµĪøĪæĪ“ĪæĪ»ĪæĪ³Ī¹ĪŗĻ ĻĪ»Ī±ĪÆĻĪ¹Īæ, ĻĻĪæĻĪµĪÆĪ½ĪæĪ½ĻĪ±Ī¹ Ī½ĪĪ± Ī±ĻĻĪ¹ĻĪµĪŗĻĪæĪ½Ī¹ĪŗĪ¬ ĻĻĻĻĻ
ĻĪ± ĻĪæĻ
ĻĻĪæĻĪµĻĪæĻ
Ī½ ĻĻĪ· Ī³ĪµĻĻĻĻĻĪ· ĻĪæĻ
ĻĪ¬ĻĪ¼Ī±ĻĪæĻ Ī¼ĪµĻĪ±Ī¾Ļ ĻĪ·Ļ ĻĻĪµĪ“Ī¹Ī±ĻĻĪ¹ĪŗĪ®Ļ ĻĪæĪ»Ļ
ĻĪ»ĪæĪŗĻĻĪ·ĻĪ±Ļ ĪŗĪ±Ī¹ ĻĪ·Ļ ĻĪµĻĪ½ĪæĪ»ĪæĪ³Ī¹ĪŗĪ®Ļ ĻĪ±ĻĪ±Ī³ĻĪ³Ī¹ĪŗĻĻĪ·ĻĪ±Ļ, Ī¼Īµ ĻĪ· ĻĻĪ®ĻĪ· ĻĻ
ĻĻĪ·Ī¼Ī¬ĻĻĪ½ ĪµĪ¾ĪµĪ¹Ī“Ī¹ĪŗĪµĻ
Ī¼ĪĪ½ĻĪ½ ĪµĻĪ¹ĻĪ±ĻĻ
Ī½ĻĻĪ½ Ļ
Ī»Ī¹ĪŗĪæĻ ĻĪµ ĪµĻĪµĻĪæĪ³ĪµĪ½Ī® ĻĻ
ĻĻĪ®Ī¼Ī±ĻĪ±-ĻĪµ-ĻĪ·ĻĪÆĪ“Ī± ĪŗĪ±ĪøĻĻ ĪŗĪ±Ī¹ Ī“ĪÆĪŗĻĻ
Ī±-ĻĪµ-ĻĪ·ĻĪÆĪ“Ī±. Ī Ī±ĻĪæĻ
ĻĪ¹Ī¬Ī¶ĪµĻĪ±Ī¹ ĪŗĪ±ĻĪ¬Ī»Ī»Ī·Ī»Ī· Ī¼ĪµĪøĪæĪ“ĪæĪ»ĪæĪ³ĪÆĪ± ĻĻ
Ī½-ĻĻĪµĪ“ĪÆĪ±ĻĪ·Ļ ĻĻĪ½ ĪµĻĪ¹ĻĪ±ĻĻ
Ī½ĻĻĪ½ Ļ
Ī»Ī¹ĪŗĪæĻ ĪŗĪ±Ī¹ ĻĪæĻ
Ī»ĪæĪ³Ī¹ĻĪ¼Ī¹ĪŗĪæĻ ĻĻĪæĪŗĪµĪ¹Ī¼ĪĪ½ĪæĻ
Ī½Ī± Ī±ĻĪæĻĪ±ĻĪ¹ĻĪøĪµĪÆ Ī· ĪŗĪ±ĻĪ±Ī½ĪæĪ¼Ī® ĻĻĪ½ ĪµĻĪ³Ī±ĻĪ¹ĻĪ½ ĻĻĪæĻ
Ļ Ī“Ī¹Ī±ĪøĪĻĪ¹Ī¼ĪæĻ
Ļ ĻĻĻĪæĻ
Ļ ĻĪæĻ
ĻĻ
ĻĻĪ®Ī¼Ī±ĻĪæĻ/Ī“Ī¹ĪŗĻĻĪæĻ
. Ī¤Īæ Ī¼ĪµĪøĪæĪ“ĪæĪ»ĪæĪ³Ī¹ĪŗĻ ĻĪ»Ī±ĪÆĻĪ¹Īæ ĻĻĪæĪ²Ī»ĪĻĪµĪ¹ ĻĪ·Ī½ Ļ
Ī»ĪæĻĪæĪÆĪ·ĻĪ· ĻĻĪ½ ĪµĻĪ¹ĻĪ±ĻĻ
Ī½ĻĻĪ½ ĪµĪÆĻĪµ Ī¼Īµ ĻĻ
Ī¼Ī²Ī±ĻĪ¹ĪŗĪĻ Ī¼ĪµĪøĻĪ“ĪæĻ
Ļ ĻĻĪæĪ³ĻĪ±Ī¼Ī¼Ī±ĻĪ¹ĻĪ¼ĪæĻ ĻĪµ Ī³Ī»ĻĻĻĪ± ĻĪµĻĪ¹Ī³ĻĪ±ĻĪ®Ļ Ļ
Ī»Ī¹ĪŗĪæĻ ĪµĪÆĻĪµ Ī¼Īµ Ī±ĻĪ±Ī¹ĻĪµĻĪ¹ĪŗĻ ĻĻĪæĪ³ĻĪ±Ī¼Ī¼Ī±ĻĪ¹ĻĻĪ¹ĪŗĻ Ī¼ĪæĪ½ĻĪĪ»Īæ Ī¼Īµ ĻĪ· ĻĻĪ®ĻĪ· ĻĪµĻĪ½Ī¹ĪŗĻĪ½ Ļ
ĻĪ·Ī»ĪæĻ ĪµĻĪ¹ĻĪĪ“ĪæĻ
ĻĻĪ½ĪøĪµĻĪ·Ļ. Ī£Īµ ĪŗĪ¬ĪøĪµ ĻĪµĻĪÆĻĻĻĻĪ·, Ī“ĪÆĪ“ĪµĻĪ±Ī¹ Ī· Ī“Ļ
Ī½Ī±ĻĻĻĪ·ĻĪ± ĻĻĪæ ĻĻĪµĪ“Ī¹Ī±ĻĻĪ® Ī³Ī¹Ī± Ī²ĪµĪ»ĻĪ¹ĻĻĪæĻĪæĪÆĪ·ĻĪ· ĻĻ
ĻĻĪ·Ī¼Ī¹ĪŗĻĪ½ Ī¼ĪµĻĻĪ¹ĪŗĻĪ½, ĻĻĻĻ Ī· ĻĪ±ĻĻĻĪ·ĻĪ± ĪµĻĪµĪ¾ĪµĻĪ³Ī±ĻĪÆĪ±Ļ, Ī· ĻĻ
ĪøĪ¼Ī±ĻĻĪ“ĪæĻĪ·, Ī· Ī±Ī¾Ī¹ĪæĻĪ¹ĻĻĪÆĪ±, Ī· ĪŗĪ±ĻĪ±Ī½Ī¬Ī»ĻĻĪ· ĪµĪ½ĪĻĪ³ĪµĪ¹Ī±Ļ ĪŗĪ±Ī¹ Ī· ĪµĻĪ¹ĻĪ¬Ī½ĪµĪ¹Ī± ĻĻ
ĻĪ¹ĻĪÆĪæĻ
ĻĪæĻ
ĻĻĪµĪ“Ī¹Ī±ĻĪ¼ĪæĻ. Ī¤ĪĪ»ĪæĻ, ĻĻĪæĪŗĪµĪ¹Ī¼ĪĪ½ĪæĻ
Ī½Ī± Ī±Ī½ĻĪ¹Ī¼ĪµĻĻĻĪ¹ĻĪøĪµĪÆ Ī· Ī±Ļ
Ī¾Ī·Ī¼ĪĪ½Ī· ĻĪæĪ»Ļ
ĻĪ»ĪæĪŗĻĻĪ·ĻĪ± ĻĻĪ± ĻĻĪµĪ“Ī¹Ī±ĻĻĪ¹ĪŗĪ¬ ĪµĻĪ³Ī±Ī»ĪµĪÆĪ± ĪµĻĪ±Ī½Ī±Ī“Ī¹Ī±Ī¼ĪæĻĻĪæĻĪ¼ĪµĪ½ĻĪ½ ĻĻ
ĻĻĪ·Ī¼Ī¬ĻĻĪ½, ĻĻĪæĻĪµĪÆĪ½ĪæĪ½ĻĪ±Ī¹ Ī½ĪĪæĪ¹ ĪµĪ¾ĪµĪ»Ī¹ĪŗĻĪ¹ĪŗĪæĪÆ Ī±Ī»Ī³ĻĻĪ¹ĪøĪ¼ĪæĪ¹ ĻĪæĪ»Ļ
ĪŗĻĪ¹ĻĪ·ĻĪ¹Ī±ĪŗĪ®Ļ Ī²ĪµĪ»ĻĪ¹ĻĻĪæĻĪæĪÆĪ·ĻĪ·Ļ, ĪæĪ¹ ĪæĻĪæĪÆĪæĪ¹ ĪµĪŗĪ¼ĪµĻĪ±Ī»Ī»ĪµĻ
ĻĪ¼ĪµĪ½ĪæĪ¹ ĻĪæĻ
Ļ ĻĻĪ³ĻĻĪæĪ½ĪæĻ
Ļ ĻĪæĪ»Ļ
ĻĻĻĪ·Ī½ĪæĻ
Ļ ĪµĻĪµĪ¾ĪµĻĪ³Ī±ĻĻĪĻ ĪŗĪ±Ī¹ ĻĪ·Ī½ Ī±Ī“ĻĪæĪ¼ĪµĻĪ® ĻĻĻĪ· ĻĻĪ½ ĻĪæĪ»Ļ
Ī½Ī·Ī¼Ī±ĻĪ¹ĪŗĻĪ½ ĻĪµĻĪ¹Ī²Ī±Ī»Ī»ĻĪ½ĻĻĪ½ ĻĻĪæĪ³ĻĪ±Ī¼Ī¼Ī±ĻĪ¹ĻĪ¼ĪæĻ (Ļ.Ļ. OpenMP), Ī¼ĪµĪ¹ĻĪ½ĪæĻ
Ī½ ĻĪæ ĻĻĻĪ½Īæ ĪµĻĪÆĪ»Ļ
ĻĪ·Ļ ĻĪæĻ
ĻĻĪæĪ²Ī»Ī®Ī¼Ī±ĻĪæĻ ĻĪ·Ļ ĻĪæĻĪæĪøĪĻĪ·ĻĪ·Ļ ĻĻĪ½ Ī»ĪæĪ³Ī¹ĪŗĻĪ½ ĻĻĻĻĪ½ ĻĪµ ĻĻ
ĻĪ¹ĪŗĪæĻĻ,ĪµĪ½Ļ ĻĪ±Ļ
ĻĻĻĻĪæĪ½Ī±, ĪæĪ¼Ī±Ī“ĪæĻĪæĪ¹ĻĪ½ĻĪ±Ļ ĻĪ¹Ļ ĪµĻĪ±ĻĪ¼ĪæĪ³ĪĻ Ī²Ī¬ĻĪ· ĻĻĪ½ ĪµĪ³Ī³ĪµĪ½ĻĪ½ ĻĪ±ĻĪ±ĪŗĻĪ·ĻĪ¹ĻĻĪ¹ĪŗĻĪ½ ĻĪæĻ
Ļ, Ī“Ī¹ĪµĻĪµĻ
Ī½ĪæĻĪ½ Ī±ĻĪæĻĪµĪ»ĪµĻĪ¼Ī±ĻĪ¹ĪŗĻĻĪµĻĪ± ĻĪæ ĻĻĻĪæ ĻĻĪµĪ“ĪÆĪ±ĻĪ·Ļ.Ī Ī±ĻĪæĪ“ĪæĻĪ¹ĪŗĻĻĪ·ĻĪ¬ ĻĻĪ½ ĻĻĪæĻĪµĪ¹Ī½ĻĪ¼ĪµĪ½ĻĪ½ Ī±ĻĻĪ¹ĻĪµĪŗĻĪæĪ½Ī¹ĪŗĻĪ½ ĻĻĪæĻĻĻĻĪ½ ĪŗĪ±Ī¹ Ī¼ĪµĪøĪæĪ“ĪæĪ»ĪæĪ³Ī¹ĻĪ½ ĪµĻĪ±Ī»Ī·ĪøĪµĻĻĪ·ĪŗĪµ ĻĪµ ĻĻĪĻĪ· Ī¼Īµ ĻĪ¹Ļ Ļ
ĻĪ¹ĻĻĪ¬Ī¼ĪµĪ½ĪµĻ Ī»ĻĻĪµĪ¹Ļ Ī±Ī¹ĻĪ¼Ī®Ļ ĻĻĻĪæ ĻĪµ Ī±Ļ
ĻĪæĻĪµĪ»Ī®Ļ ĪµĻĪ±ĻĪ¼ĪæĪ³ĪĻ, ĻĻĻĻ Ī· ĻĪ·ĻĪ¹Ī±ĪŗĪ® ĪµĻĪµĪ¾ĪµĻĪ³Ī±ĻĪÆĪ± ĻĪ®Ī¼Ī±ĻĪæĻ, ĻĪ± ĻĪæĪ»Ļ
Ī¼ĪĻĪ± ĪŗĪ±Ī¹ ĻĪ± ĻĻĪæĪ²Ī»Ī®Ī¼Ī±ĻĪ± Ī±ĻĪ¹ĪøĪ¼Ī·ĻĪ¹ĪŗĪ®Ļ ĻĪæĪ»Ļ
ĻĪ»ĪæĪŗĻĻĪ·ĻĪ±Ļ, ĪŗĪ±ĪøĻĻ ĪŗĪ±Ī¹ ĻĪµ ĻĻ
ĻĻĪ·Ī¼Ī¹ĪŗĪ¬ ĪµĻĪµĻĪæĪ³ĪµĪ½Ī® ĻĪµĻĪ¹Ī²Ī¬Ī»Ī»ĪæĪ½ĻĪ±, ĻĻĻĻ ĪĪ½Ī± ĻĻĻĻĪ·Ī¼Ī± ĻĻĪ±ĻĪ·Ļ Ļ
ĻĪæĪ»ĪæĪ³Ī¹ĻĻĻĪ½ Ī³Ī¹Ī± Ī±Ļ
ĻĻĪ½ĪæĪ¼Ī± Ī“Ī¹Ī±ĻĻĪ·Ī¼Ī¹ĪŗĪ¬ ĻĪæĪ¼ĻĪæĻĪ¹ĪŗĪ¬ ĪæĻĪ®Ī¼Ī±ĻĪ± ĪŗĪ±Ī¹ ĪĪ½Ī± ĻĻĻĻĪ·Ī¼Ī± ĻĪæĪ»Ī»Ī±ĻĪ»ĻĪ½ ĪµĻĪ¹ĻĪ±ĻĻ
Ī½ĻĻĪ½ Ļ
Ī»Ī¹ĪŗĪæĻ Ī³Ī¹Ī± ĻĻĪ±ĪøĪ¼ĪæĻĻ ĪµĻĪ³Ī±ĻĪÆĪ±Ļ ĪŗĪ±Ī¹ ĪŗĪĪ½ĻĻĪ± Ī“ĪµĪ“ĪæĪ¼ĪĪ½ĻĪ½, ĻĻĪæĻĪµĻĪæĪ½ĻĪ±Ļ ĪµĻĪ±ĻĪ¼ĪæĪ³ĪĻ Ļ
ĻĪ·Ī»Ī®Ļ Ļ
ĻĪæĪ»ĪæĪ³Ī¹ĻĻĪ¹ĪŗĪ®Ļ Ī±ĻĻĪ“ĪæĻĪ·Ļ (HPC). Ī¤Ī± Ī±ĻĪæĻĪµĪ»ĪĻĪ¼Ī±ĻĪ± ĪµĪ½Ī¹ĻĻĻĪæĻ
Ī½ ĻĪ·Ī½ ĻĪµĻĪæĪÆĪøĪ·ĻĪ· ĻĪæĻ
Ī³ĻĪ¬ĻĪæĪ½ĻĪ±, ĻĻĪ¹ Ī· ĻĪ±ĻĪæĻĻĪ± Ī“Ī¹Ī±ĻĻĪ¹Ī²Ī® ĻĪ±ĻĪĻĪµĪ¹ Ī±Ī½ĻĪ±Ī³ĻĪ½Ī¹ĻĻĪ¹ĪŗĪ® ĻĪµĻĪ½ĪæĪ³Ī½ĻĻĪÆĪ± Ī³Ī¹Ī± ĻĪ·Ī½ Ī±Ī½ĻĪ¹Ī¼ĪµĻĻĻĪ¹ĻĪ· ĻĻĪ½ ĻĪæĪ»ĻĻĪ»ĪæĪŗĻĪ½ ĻĻĪ³ĻĻĪæĪ½ĻĪ½ ĪŗĪ±Ī¹ ĻĻĪæĪ²Ī»ĪµĻĻĪ¼ĪµĪ½Ī± Ī¼ĪµĪ»Ī»ĪæĪ½ĻĪ¹ĪŗĻĪ½ ĻĻĪµĪ“Ī¹Ī±ĻĻĪ¹ĪŗĻĪ½ ĻĻĪæĪŗĪ»Ī®ĻĪµĻĪ½
A Finite Domain Constraint Approach for Placement and Routing of Coarse-Grained Reconfigurable Architectures
Scheduling, placement, and routing are important steps in Very Large Scale Integration (VLSI) design. Researchers have developed numerous techniques to solve placement and routing problems. As the complexity of Application Specific Integrated Circuits (ASICs) increased over the past decades, so did the demand for improved place and route techniques. The primary objective of these place and route approaches has typically been wirelength minimization due to its impact on signal delay and design performance. With the advent of Field Programmable Gate Arrays (FPGAs), the same place and route techniques were applied to FPGA-based design. However, traditional place and route techniques may not work for Coarse-Grained Reconfigurable Architectures (CGRAs), which are reconfigurable devices offering wider path widths than FPGAs and more flexibility than ASICs, due to the differences in architecture and routing network. Further, the routing network of several types of CGRAs, including the Field Programmable Object Array (FPOA), has deterministic timing as compared to the routing fabric of most ASICs and FPGAs reported in the literature. This necessitates a fresh look at alternative approaches to place and route designs. This dissertation presents a finite domain constraint-based, delay-aware placement and routing methodology targeting an FPOA. The proposed methodology takes advantage of the deterministic routing network of CGRAs to perform a delay aware placement
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Efficient architectures and power modelling of multiresolution analysis algorithms on FPGA
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In the past two decades, there has been huge amount of interest in Multiresolution Analysis Algorithms (MAAs) and their applications. Processing some of their applications such as medical imaging are computationally intensive, power hungry and requires large amount of memory which cause a high demand for efficient algorithm implementation, low power architecture and acceleration. Recently, some MAAs such as Finite Ridgelet Transform (FRIT) Haar Wavelet Transform (HWT) are became very popular and they are suitable for a number of image processing applications such as detection of line singularities and contiguous edges, edge detection (useful for compression and feature detection), medical image denoising and segmentation. Efficient hardware implementation and acceleration of these algorithms particularly when addressing large problems are becoming very chal-lenging and consume lot of power which leads to a number of issues including mobility, reliability concerns. To overcome the computation problems, Field Programmable Gate Arrays (FPGAs) are the technology of choice for accelerating computationally intensive applications due to their high performance. Addressing the power issue requires optimi- sation and awareness at all level of abstractions in the design flow.
The most important achievements of the work presented in this thesis are summarised
here.
Two factorisation methodologies for HWT which are called HWT Factorisation Method1 and (HWTFM1) and HWT Factorasation Method2 (HWTFM2) have been explored to increase number of zeros and reduce hardware resources. In addition, two novel efficient and optimised architectures for proposed methodologies based on Distributed Arithmetic (DA) principles have been proposed. The evaluation of the architectural results have shown that the proposed architectures results have reduced the arithmetics calculation (additions/subtractions) by 33% and 25% respectively compared to direct implementa-tion of HWT and outperformed existing results in place. The proposed HWTFM2 is implemented on advanced and low power FPGA devices using Handel-C language. The FPGAs implementation results have outperformed other existing results in terms of area and maximum frequency. In addition, a novel efficient architecture for Finite Radon Trans-form (FRAT) has also been proposed. The proposed architecture is integrated with the developed HWT architecture to build an optimised architecture for FRIT. Strategies such as parallelism and pipelining have been deployed at the architectural level for efficient im-plementation on different FPGA devices. The proposed FRIT architecture performance has been evaluated and the results outperformed some other existing architecture in place. Both FRAT and FRIT architectures have been implemented on FPGAs using Handel-C language. The evaluation of both architectures have shown that the obtained results out-performed existing results in place by almost 10% in terms of frequency and area. The proposed architectures are also applied on image data (256 Ā£ 256) and their Peak Signal to Noise Ratio (PSNR) is evaluated for quality purposes.
Two architectures for cyclic convolution based on systolic array using parallelism and pipelining which can be used as the main building block for the proposed FRIT architec-ture have been proposed. The first proposed architecture is a linear systolic array with pipelining process and the second architecture is a systolic array with parallel process. The second architecture reduces the number of registers by 42% compare to first architec-ture and both architectures outperformed other existing results in place. The proposed pipelined architecture has been implemented on different FPGA devices with vector size (N) 4,8,16,32 and word-length (W=8). The implementation results have shown a signifi-cant improvement and outperformed other existing results in place.
Ultimately, an in-depth evaluation of a high level power macromodelling technique for design space exploration and characterisation of custom IP cores for FPGAs, called func-tional level power modelling approach have been presented. The mathematical techniques that form the basis of the proposed power modeling has been validated by a range of custom IP cores. The proposed power modelling is scalable, platform independent and compares favorably with existing approaches. A hybrid, top-down design flow paradigm integrating functional level power modelling with commercially available design tools for systematic optimisation of IP cores has also been developed. The in-depth evaluation of this tool enables us to observe the behavior of different custom IP cores in terms of power consumption and accuracy using different design methodologies and arithmetic techniques on virous FPGA platforms. Based on the results achieved, the proposed model accuracy is almost 99% true for all IP core's Dynamic Power (DP) components.Thomas Gerald Gray Charitable Trus
An Energy and Performance Exploration of Network-on-Chip Architectures
In this paper, we explore the designs of a circuit-switched router, a wormhole router, a quality-of-service (QoS) supporting virtual channel router and a speculative virtual channel router and accurately evaluate the energy-performance tradeoffs they offer. Power results from the designs placed and routed in a 90-nm CMOS process show that all the architectures dissipate significant idle state power. The additional energy required to route a packet through the router is then shown to be dominated by the data path. This leads to the key result that, if this trend continues, the use of more elaborate control can be justified and will not be immediately limited by the energy budget. A performance analysis also shows that dynamic resource allocation leads to the lowest network latencies, while static allocation may be used to meet QoS goals. Combining the power and performance figures then allows an energy-latency product to be calculated to judge the efficiency of each of the networks. The speculative virtual channel router was shown to have a very similar efficiency to the wormhole router, while providing a better performance, supporting its use for general purpose designs. Finally, area metrics are also presented to allow a comparison of implementation costs
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