890 research outputs found

    A highly parameterized and efficient FPGA-based skeleton for pairwise biological sequence alignment

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    Smart technologies for effective reconfiguration: the FASTER approach

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    Current and future computing systems increasingly require that their functionality stays flexible after the system is operational, in order to cope with changing user requirements and improvements in system features, i.e. changing protocols and data-coding standards, evolving demands for support of different user applications, and newly emerging applications in communication, computing and consumer electronics. Therefore, extending the functionality and the lifetime of products requires the addition of new functionality to track and satisfy the customers needs and market and technology trends. Many contemporary products along with the software part incorporate hardware accelerators for reasons of performance and power efficiency. While adaptivity of software is straightforward, adaptation of the hardware to changing requirements constitutes a challenging problem requiring delicate solutions. The FASTER (Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration) project aims at introducing a complete methodology to allow designers to easily implement a system specification on a platform which includes a general purpose processor combined with multiple accelerators running on an FPGA, taking as input a high-level description and fully exploiting, both at design time and at run time, the capabilities of partial dynamic reconfiguration. The goal is that for selected application domains, the FASTER toolchain will be able to reduce the design and verification time of complex reconfigurable systems providing additional novel verification features that are not available in existing tool flows

    Cross-Layer Rapid Prototyping and Synthesis of Application-Specific and Reconfigurable Many-accelerator Platforms

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    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 ”Internet of Things”. 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.ΟÎč Ï„Î”Ï‡ÎœÎżÎ»ÎżÎłÎčÎșές Î”ÎŸÎ”Î»ÎŻÎŸÎ”Îčς τωΜ Ï„Î”Î»Î”Ï…Ï„Î±ÎŻÏ‰Îœ ΔτώΜ έΞΔσαΜ τα ΞΔΌέλÎčα Î”ÎŽÏÎ±ÎŻÏ‰ÏƒÎ·Ï‚ της Ï€Î»Î·ÏÎżÏ†ÎżÏÎčÎżÏ€ÎżÎŻÎ·ÏƒÎ·Ï‚ της ÎșÎżÎčÎœÏ‰ÎœÎŻÎ±Ï‚, ΔπÎčΎρώΜτας σΔ ÎżÎčÎșÎżÎœÎżÎŒÎčÎșές,Ï€ÎżÎ»ÎčτÎčÎșές, Ï€ÎżÎ»ÎčτÎčστÎčÎșές ÎșαÎč ÎșÎżÎčΜωΜÎčÎșές ÎŽÎčÎ±ÏƒÏ„ÎŹÏƒÎ”Îčς. ÎŁÏ„Îż Î±Ï€ÏŒÎłÎ”ÎčÎż Î±Ï…Ï„ÎźÏ‚ τη Ï‚Ï€ÏÎ±ÎłÎŒÎŹÏ„Ï‰ÏƒÎ·Ï‚, ÏƒÎźÎŒÎ”ÏÎ±, ÎżÎ»ÎżÎ­ÎœÎ± ÎșαÎč πΔρÎčσσότΔρΔς ÎșαΞηΌΔρÎčΜές συσÎșΔυές ÏƒÏ…ÎœÎŽÎ­ÎżÎœÏ„Î±Îč ÏƒÏ„Îż Ï€Î±ÎłÎșόσΌÎčÎż Îčστό, Î±Ï€ÎżÎŽÎŻÎŽÎżÎœÏ„Î±Ï‚ Ï„ÎżÎœ ÏŒÏÎż «ΊΜτΔρΜΔτ τωΜ Ï€ÏÎ±ÎłÎŒÎŹÏ„Ï‰ÎœÂ».΀ο ÎŒÎ­Î»Î»ÎżÎœ ΔπÎčÏ†Ï…Î»ÎŹÏƒÏƒÎ”Îč τηΜ Ï€Î»ÎźÏÎ· σύΜΎΔση ÎșαÎč Î±Î»Î»Î·Î»Î”Ï€ÎŻÎŽÏÎ±ÏƒÎ· τωΜ ÏƒÏ…ÏƒÏ„Î·ÎŒÎŹÏ„Ï‰Îœ Ï€Î»Î·ÏÎżÏ†ÎżÏÎčÎșÎźÏ‚ ÎșαÎč ΔπÎčÎșÎżÎčΜωΜÎčώΜ ΌΔ Ï„ÎżÎœ φυσÎčÎșό ÎșÏŒÏƒÎŒÎż, ÎżÏÎčÎżÎžÎ”Ï„ÏŽÎœÏ„Î±Ï‚ τη ÎŒÎ”Ï„ÎŹÎČαση στα ÏƒÏ…ÏƒÏ„ÎźÎŒÎ±Ï„Î± φυσÎčÎșÎżÏ ÎșυÎČÎ”ÏÎœÎżÏ‡ÏŽÏÎżÏ… ÎșαÎč Ï€ÏÎżÏƒÏ†Î­ÏÎżÎœÏ„Î±Ï‚ ÎŒÎ”Ï„Î±Ï…Ï€Î·ÏÎ”ÏƒÎŻÎ”Ï‚ ÏƒÏ„ÎżÎœ φυσÎčÎșό ÎșÏŒÏƒÎŒÎż όπως Ï€ÏÎżÏƒÏ‰Ï€ÎżÏ€ÎżÎčηΌέΜη ÎčατρÎčÎșÎź Ï€Î”ÏÎŻÎžÎ±Î»ÏˆÎ·, Î±Ï…Ï„ÏŒÎœÎżÎŒÎ”Ï‚ ΌΔταÎșÎčÎœÎźÏƒÎ”Îčς, έΟυπΜΔς Î”ÎœÎ”ÏÎłÎ”ÎčαÎșÎŹ πόλΔÎčς Îș.α. . ÎŁÎșÎčÎ±ÎłÏÎ±Ï†ÏŽÎœÏ„Î±Ï‚ τÎčς Î±ÎœÎŹÎłÎșΔς Î±Ï…Ï„ÎźÏ‚ της ΎυΜαΌÎčÎșÎŹ ΔΟΔλÎčσσόΌΔΜης Î±ÎłÎżÏÎŹÏ‚, ÎżÎč ΌηχαΜÎčÎșοί Ï…Ï€ÎżÎ»ÎżÎłÎčστώΜ ÎșÎ±Î»ÎżÏÎœÏ„Î±Îč Μα Ï…Î»ÎżÏ€ÎżÎčÎźÏƒÎżÏ…Îœ Ï…Ï€ÎżÎ»ÎżÎłÎčστÎčÎșές πλατφόρΌΔς Ï€ÎżÏ… αφΔΜός Î”ÎœÏƒÏ‰ÎŒÎ±Ï„ÏŽÎœÎżÏ…Îœ αυΟηΌέΜη συστηΌÎčÎșÎź Ï€ÎżÎ»Ï…Ï€Î»ÎżÎșότητα ÎșαÎč Î±Ï†Î”Ï„Î­ÏÎżÏ… ÎșÎ±Î»ÏÏ€Ï„ÎżÏ…Îœ έΜα Δυρύ Ï†ÎŹÏƒÎŒÎ± ΌΔταχαραÎșτηρÎčστÎčÎșώΜ, όπως λ.χ. Ï„Îż ÎșÏŒÏƒÏ„ÎżÏ‚ σχΔΎÎčÎ±ÏƒÎŒÎżÏ, Îż Ï‡ÏÏŒÎœÎżÏ‚ σχΔΎÎčÎ±ÏƒÎŒÎżÏ, η αΟÎčÎżÏ€ÎčÏƒÏ„ÎŻÎ± ÎșαÎč η ΔπαΜαχρησÎčÎŒÎżÏ€ÎżÎŻÎ·ÏƒÎ·, τα ÎżÏ€ÎżÎŻÎ± Ï€ÏÎżÎŽÎčÎ±ÎłÏÎŹÏ†ÎżÎœÏ„Î±Îč από έΜα αΜτÎčÎșÏÎżÏ…ÏŒÎŒÎ”ÎœÎż ÏƒÏÎœÎżÎ»Îż λΔÎčÏ„ÎżÏ…ÏÎłÎčÎșώΜ, Ï„Î”Ï‡ÎœÎżÎ»ÎżÎłÎčÎșώΜ ÎșαÎč ÎșατασÎșΔυαστÎčÎșώΜ πΔρÎčÎżÏÎčσΌώΜ. Η Ï€Î±ÏÎżÏÏƒÎ± ÎŽÎčατρÎčÎČÎź ÏƒÏ„ÎżÏ‡Î”ÏÎ”Îč στηΜ αΜτÎčΌΔτώπÎčση τωΜ Ï€Î±ÏÎ±Ï€ÎŹÎœÏ‰ σχΔΎÎčαστÎčÎșώΜ Ï€ÏÎżÎșÎ»ÎźÏƒÎ”Ï‰Îœ, Όέσω της Î±ÎœÎŹÏ€Ï„Ï…ÎŸÎ·Ï‚ ÎŒÎ”ÎžÎżÎŽÎżÎ»ÎżÎłÎčώΜ ÎșαÎč Î”ÏÎłÎ±Î»Î”ÎŻÏ‰Îœ ÏƒÏ…ÎœÏƒÏ‡Î”ÎŽÎŻÎ±ÏƒÎ·Ï‚ υλÎčÎșÎżÏ/λογÎčσΌÎčÎșÎżÏ Ï€ÎżÏ… ΔπÎčÏ„ÏÎ­Ï€ÎżÏ…Îœ τηΜ Ï„Î±Ï‡Î”ÎŻÎ± Ï…Î»ÎżÏ€ÎżÎŻÎ·ÏƒÎ· ÎșαΞώς ÎșαÎč τηΜ Î±Ï€ÎżÎŽÎżÏ„ÎčÎșÎź σύΜΞΔση αρχÎčτΔÎșÏ„ÎżÎœÎčÎșώΜ λύσΔωΜ, ÎżÎč ÎżÏ€ÎżÎŻÎ”Ï‚ Ï€ÏÎżÎŽÎčÎ±ÎłÏÎŹÏ†ÎżÏ…Îœ τα ΌΔτα-χαραÎșτηρÎčστÎčÎșÎŹ λΔÎčÏ„ÎżÏ…ÏÎłÎŻÎ±Ï‚ Ï€ÎżÏ… απαÎčÏ„Î”ÎŻ η ÏƒÏÎłÏ‡ÏÎżÎœÎ· Î±ÎłÎżÏÎŹ. ÎŁÏ…ÎłÎșΔÎșρÎčΌέΜα, στα Ï€Î»Î±ÎŻÏƒÎčα Î±Ï…Ï„ÎźÏ‚ της ÎŽÎčατρÎčÎČÎźÏ‚, Ï€Î±ÏÎżÏ…ÏƒÎčÎŹÎ¶ÎżÎœÏ„Î±Îč α) ÎŒÎ”ÎžÎżÎŽÎżÎ»ÎżÎłÎŻÎ”Ï‚ ΔπÎčÏ„ÎŹÏ‡Ï…ÎœÏƒÎ·Ï‚ της ÏÎżÎźÏ‚ σχΔΎÎčÎ±ÏƒÎŒÎżÏ Ï„ÏŒÏƒÎż ÎłÎčα ΔπαΜαΎÎčÎ±ÎŒÎżÏÏ†ÎżÏÎŒÎ”ÎœÎ”Ï‚ ÏŒÏƒÎż ÎșαÎč ÎłÎčα ΔΟΔÎčÎŽÎčÎșΔυΌέΜΔς αρχÎčτΔÎșÏ„ÎżÎœÎčÎșές, ÎČ) Î”Ï„Î”ÏÎżÎłÎ”ÎœÎź Î±ÎŽÏÎżÎŒÎ”ÏÎź αρχÎčτΔÎșÏ„ÎżÎœÎčÎșÎŹ πρότυπα ΔπÎčÏ„ÎŹÏ‡Ï…ÎœÏƒÎ·Ï‚ Î”Ï€Î”ÎŸÎ”ÏÎłÎ±ÏƒÎŻÎ±Ï‚ ÎșαÎč ΔπÎčÎșÎżÎčÎœÏ‰ÎœÎŻÎ±Ï‚ ÎșαÎč Îł) Î±Ï€ÎżÎŽÎżÏ„ÎčÎșές τΔχΜÎčÎșές Ï€ÎżÎ»Ï…ÎșρÎčτηρÎčαÎșÎźÏ‚ σύΜΞΔσης Ï„ÏŒÏƒÎż σΔ υψηλό αφαÎčρΔτÎčÎșό Î”Ï€ÎŻÏ€Î”ÎŽÎż Ï€ÏÎżÎłÏÎ±ÎŒÎŒÎ±Ï„ÎčÏƒÎŒÎżÏ,ÏŒÏƒÎż ÎșαÎč σΔ φυσÎčÎșό Î”Ï€ÎŻÏ€Î”ÎŽÎż πυρÎčÏ„ÎŻÎżÏ….Î‘ÎœÎ±Ï†ÎżÏÎčÎșÎŹ Ï€ÏÎżÏ‚ τηΜ ΔπÎčÏ„ÎŹÏ‡Ï…ÎœÏƒÎ· της ÏÎżÎźÏ‚ σχΔΎÎčÎ±ÏƒÎŒÎżÏ, Ï€ÏÎżÏ„Î”ÎŻÎœÎ”Ï„Î±Îč ÎŒÎčα ÎŒÎ”ÎžÎżÎŽÎżÎ»ÎżÎłÎŻÎ± Ï€ÎżÏ… χρησÎčÎŒÎżÏ€ÎżÎčΔί ΔÎčÎșÎżÎœÎčÎșές πλατφόρΌΔς, ÎżÎč ÎżÏ€ÎżÎŻÎ”Ï‚ αφαÎčρώΜτας τÎčς αρχÎčτΔÎșÏ„ÎżÎœÎčÎșές Î»Î”Ï€Ï„ÎżÎŒÎ­ÏÎ”ÎčΔς ÎșÎ±Ï„Î±Ï†Î­ÏÎœÎżÏ…Îœ Μα ΌΔÎčÏŽÏƒÎżÏ…Îœ σηΌαΜτÎčÎșÎŹ Ï„Îż Ï‡ÏÏŒÎœÎż Î”ÎŸÎżÎŒÎżÎŻÏ‰ÏƒÎ·Ï‚. Î Î±ÏÎŹÎ»Î»Î·Î»Î±, ΔÎčÏƒÎ·ÎłÎ”ÎŻÏ„Î±Îč η συστηΌÎčÎșÎź συΜ-Î”ÎŸÎżÎŒÎżÎŻÏ‰ÏƒÎ· ΌΔ τη Ï‡ÏÎźÏƒÎ· ΔπαΜαΎÎčÎ±ÎŒÎżÏÏ†ÎżÏÎŒÎ”ÎœÏ‰Îœ Ï€Î»Î±Ï„Ï†ÎżÏÎŒÏŽÎœ, ως ΌέσωΜ ΔπÎčÏ„ÎŹÏ‡Ï…ÎœÏƒÎ·Ï‚. ΜΔ αυτόΜ Ï„ÎżÎœ Ï„ÏÏŒÏ€Îż, Îż ÎșύÎșÎ»ÎżÏ‚ Î±ÎœÎŹÏ€Ï„Ï…ÎŸÎ·Ï‚ ΔΜός Ï€ÏÎżÏŠÏŒÎœÏ„ÎżÏ‚ υλÎčÎșÎżÏ, ΌΔτατΔΞΔÎčÎŒÎ­ÎœÎżÏ‚ από τηΜ ÎșÎŹÎžÎ”Ï„Î· σΔÎčρÎčαÎșÎź ÏÎżÎź σΔ έΜαΜ ÎșυÎșλÎčÎșό αλληλΔπÎčΎραστÎčÎșό ÎČÏÏŒÎłÏ‡Îż, ÎșÎ±ÎžÎŻÏƒÏ„Î±Ï„Î±Îč Ï„Î±Ï‡ÏÏ„Î”ÏÎżÏ‚, ΔΜώ ÎżÎč ΎυΜατότητΔς Ï€ÏÎżÏƒÎżÎŒÎżÎŻÏ‰ÏƒÎ·Ï‚ Î”ÎŒÏ€Î»ÎżÏ…Ï„ÎŻÎ¶ÎżÎœÏ„Î±Îč ΌΔ Î±Ï€ÎżÎŽÎżÏ„ÎčÎșότΔρΔς ÎŒÎ”ÎžÏŒÎŽÎżÏ…Ï‚ Î”ÎœÏ„ÎżÏ€ÎčÏƒÎŒÎżÏ ÎșαÎč ÎŽÎčόρΞωσης σχΔΎÎčαστÎčÎșώΜ ÏƒÏ†Î±Î»ÎŒÎŹÏ„Ï‰Îœ, ÎșαΞώς ÎșαÎč ÎŒÎ”ÎžÏŒÎŽÎżÏ…Ï‚ Î”Î»Î­ÎłÏ‡ÎżÏ… τωΜ ΌΔτρÎčÎșώΜ Î±Ï€ÏŒÎŽÎżÏƒÎ·Ï‚ Ï„ÎżÏ… ÏƒÏ…ÏƒÏ„ÎźÎŒÎ±Ï„ÎżÏ‚ σΔ σχέση ΌΔ τÎčς ΔπÎčΞυΌητές Ï€ÏÎżÎŽÎčÎ±ÎłÏÎ±Ï†Î­Ï‚, σΔ όλΔς τÎčς Ï†ÎŹÏƒÎ”Îčς Î±ÎœÎŹÏ€Ï„Ï…ÎŸÎ·Ï‚ Ï„ÎżÏ… ÏƒÏ…ÏƒÏ„ÎźÎŒÎ±Ï„ÎżÏ‚. ΣΔ ÎżÏÎžÎżÎłÏŽÎœÎčα ÏƒÏ…ÎœÎŹÏ†Î”Îčα ΌΔ Ï„Îż Ï€ÏÎżÎ±ÎœÎ±Ï†Î”ÏÎžÎ­Îœ ÎŒÎ”ÎžÎżÎŽÎżÎ»ÎżÎłÎčÎșό Ï€Î»Î±ÎŻÏƒÎčÎż, Ï€ÏÎżÏ„Î”ÎŻÎœÎżÎœÏ„Î±Îč Μέα αρχÎčτΔÎșÏ„ÎżÎœÎčÎșÎŹ πρότυπα Ï€ÎżÏ… ÏƒÏ„ÎżÏ‡Î”ÏÎżÏ…Îœ στη ÎłÎ”Ï†ÏÏÏ‰ÏƒÎ· Ï„ÎżÏ… Ï‡ÎŹÏƒÎŒÎ±Ï„ÎżÏ‚ ΌΔταΟύ της σχΔΎÎčαστÎčÎșÎźÏ‚ Ï€ÎżÎ»Ï…Ï€Î»ÎżÎșότητας ÎșαÎč της Ï„Î”Ï‡ÎœÎżÎ»ÎżÎłÎčÎșÎźÏ‚ Ï€Î±ÏÎ±ÎłÏ‰ÎłÎčÎșότητας, ΌΔ τη Ï‡ÏÎźÏƒÎ· ÏƒÏ…ÏƒÏ„Î·ÎŒÎŹÏ„Ï‰Îœ ΔΟΔÎčÎŽÎčÎșΔυΌέΜωΜ ΔπÎčταχυΜτώΜ υλÎčÎșÎżÏ σΔ Î”Ï„Î”ÏÎżÎłÎ”ÎœÎź ÏƒÏ…ÏƒÏ„ÎźÎŒÎ±Ï„Î±-σΔ-ÏˆÎ·Ï†ÎŻÎŽÎ± ÎșαΞώς ÎșαÎč ÎŽÎŻÎșτυα-σΔ-ÏˆÎ·Ï†ÎŻÎŽÎ±. Î Î±ÏÎżÏ…ÏƒÎčÎŹÎ¶Î”Ï„Î±Îč ÎșÎ±Ï„ÎŹÎ»Î»Î·Î»Î· ÎŒÎ”ÎžÎżÎŽÎżÎ»ÎżÎłÎŻÎ± συΜ-ÏƒÏ‡Î”ÎŽÎŻÎ±ÏƒÎ·Ï‚ τωΜ ΔπÎčταχυΜτώΜ υλÎčÎșÎżÏ ÎșαÎč Ï„ÎżÏ… λογÎčσΌÎčÎșÎżÏ Ï€ÏÎżÎșΔÎčÎŒÎ­ÎœÎżÏ… Μα Î±Ï€ÎżÏ†Î±ÏƒÎčÏƒÎžÎ”ÎŻ η ÎșÎ±Ï„Î±ÎœÎżÎŒÎź τωΜ Î”ÏÎłÎ±ÏƒÎčώΜ ÏƒÏ„ÎżÏ…Ï‚ ÎŽÎčαΞέσÎčÎŒÎżÏ…Ï‚ Ï€ÏŒÏÎżÏ…Ï‚ Ï„ÎżÏ… ÏƒÏ…ÏƒÏ„ÎźÎŒÎ±Ï„ÎżÏ‚/ÎŽÎčÎșÏ„ÏÎżÏ…. ΀ο ÎŒÎ”ÎžÎżÎŽÎżÎ»ÎżÎłÎčÎșό Ï€Î»Î±ÎŻÏƒÎčÎż Ï€ÏÎżÎČλέπΔÎč τηΜ Ï…Î»ÎżÏ€ÎżÎŻÎ·ÏƒÎ· τωΜ ΔπÎčταχυΜτώΜ Î”ÎŻÏ„Î” ΌΔ συΌÎČατÎčÎșές ÎŒÎ”ÎžÏŒÎŽÎżÏ…Ï‚ Ï€ÏÎżÎłÏÎ±ÎŒÎŒÎ±Ï„ÎčÏƒÎŒÎżÏ σΔ ÎłÎ»ÏŽÏƒÏƒÎ± πΔρÎčÎłÏÎ±Ï†ÎźÏ‚ υλÎčÎșÎżÏ Î”ÎŻÏ„Î” ΌΔ αφαÎčρΔτÎčÎșό Ï€ÏÎżÎłÏÎ±ÎŒÎŒÎ±Ï„ÎčστÎčÎșό ÎŒÎżÎœÏ„Î­Î»Îż ΌΔ τη Ï‡ÏÎźÏƒÎ· τΔχΜÎčÎșώΜ Ï…ÏˆÎ·Î»ÎżÏ ΔπÎčÏ€Î­ÎŽÎżÏ… σύΜΞΔσης. ΣΔ ÎșΏΞΔ Ï€Î”ÏÎŻÏ€Ï„Ï‰ÏƒÎ·, ÎŽÎŻÎŽÎ”Ï„Î±Îč η ΎυΜατότητα ÏƒÏ„Îż σχΔΎÎčÎ±ÏƒÏ„Îź ÎłÎčα ÎČΔλτÎčÏƒÏ„ÎżÏ€ÎżÎŻÎ·ÏƒÎ· συστηΌÎčÎșώΜ ΌΔτρÎčÎșώΜ, όπως η ταχύτητα Î”Ï€Î”ÎŸÎ”ÏÎłÎ±ÏƒÎŻÎ±Ï‚, η ÏÏ…ÎžÎŒÎ±Ï€ÏŒÎŽÎżÏƒÎ·, η αΟÎčÎżÏ€ÎčÏƒÏ„ÎŻÎ±, η ÎșÎ±Ï„Î±ÎœÎŹÎ»Ï‰ÏƒÎ· Î”ÎœÎ­ÏÎłÎ”Îčας ÎșαÎč η ΔπÎčÏ†ÎŹÎœÎ”Îčα πυρÎčÏ„ÎŻÎżÏ… Ï„ÎżÏ… σχΔΎÎčÎ±ÏƒÎŒÎżÏ. Î€Î­Î»ÎżÏ‚, Ï€ÏÎżÎșΔÎčÎŒÎ­ÎœÎżÏ… Μα αΜτÎčΌΔτωπÎčÏƒÎžÎ”ÎŻ η αυΟηΌέΜη Ï€ÎżÎ»Ï…Ï€Î»ÎżÎșότητα στα σχΔΎÎčαστÎčÎșÎŹ Î”ÏÎłÎ±Î»Î”ÎŻÎ± ΔπαΜαΎÎčÎ±ÎŒÎżÏÏ†ÎżÏÎŒÎ”ÎœÏ‰Îœ ÏƒÏ…ÏƒÏ„Î·ÎŒÎŹÏ„Ï‰Îœ, Ï€ÏÎżÏ„Î”ÎŻÎœÎżÎœÏ„Î±Îč ÎœÎ­ÎżÎč ΔΟΔλÎčÎșτÎčÎșοί Î±Î»ÎłÏŒÏÎčÎžÎŒÎżÎč Ï€ÎżÎ»Ï…ÎșρÎčτηρÎčαÎșÎźÏ‚ ÎČΔλτÎčÏƒÏ„ÎżÏ€ÎżÎŻÎ·ÏƒÎ·Ï‚, ÎżÎč ÎżÏ€ÎżÎŻÎżÎč ΔÎșÎŒÎ”Ï„Î±Î»Î»Î”Ï…ÏŒÎŒÎ”ÎœÎżÎč Ï„ÎżÏ…Ï‚ ÏƒÏÎłÏ‡ÏÎżÎœÎżÏ…Ï‚ Ï€ÎżÎ»Ï…Ï€ÏÏÎ·ÎœÎżÏ…Ï‚ Î”Ï€Î”ÎŸÎ”ÏÎłÎ±ÏƒÏ„Î­Ï‚ ÎșαÎč τηΜ Î±ÎŽÏÎżÎŒÎ”ÏÎź φύση τωΜ Ï€ÎżÎ»Ï…ÎœÎ·ÎŒÎ±Ï„ÎčÎșώΜ πΔρÎčÎČαλλόΜτωΜ Ï€ÏÎżÎłÏÎ±ÎŒÎŒÎ±Ï„ÎčÏƒÎŒÎżÏ (π.χ. OpenMP), ΌΔÎčÏŽÎœÎżÏ…Îœ Ï„Îż Ï‡ÏÏŒÎœÎż Î”Ï€ÎŻÎ»Ï…ÏƒÎ·Ï‚ Ï„ÎżÏ… Ï€ÏÎżÎČÎ»ÎźÎŒÎ±Ï„ÎżÏ‚ της Ï„ÎżÏ€ÎżÎžÎ­Ï„Î·ÏƒÎ·Ï‚ τωΜ λογÎčÎșώΜ πόρωΜ σΔ φυσÎčÎșÎżÏÏ‚,ΔΜώ Ï„Î±Ï…Ï„ÏŒÏ‡ÏÎżÎœÎ±, ÎżÎŒÎ±ÎŽÎżÏ€ÎżÎčώΜτας τÎčς Î”Ï†Î±ÏÎŒÎżÎłÎ­Ï‚ ÎČÎŹÏƒÎ· τωΜ Î”ÎłÎłÎ”ÎœÏŽÎœ χαραÎșτηρÎčστÎčÎșώΜ Ï„ÎżÏ…Ï‚, ÎŽÎčÎ”ÏÎ”Ï…ÎœÎżÏÎœ Î±Ï€ÎżÏ„Î”Î»Î”ÏƒÎŒÎ±Ï„ÎčÎșότΔρα Ï„Îż Ï‡ÏŽÏÎż ÏƒÏ‡Î”ÎŽÎŻÎ±ÏƒÎ·Ï‚.Η Î±Ï€ÎżÎŽÎżÏ„ÎčÎșÏŒÏ„Î·Ï„ÎŹ τωΜ Ï€ÏÎżÏ„Î”ÎčΜόΌΔΜωΜ αρχÎčτΔÎșÏ„ÎżÎœÎčÎșώΜ Ï€ÏÎżÏ„ÏÏ€Ï‰Îœ ÎșαÎč ÎŒÎ”ÎžÎżÎŽÎżÎ»ÎżÎłÎčώΜ ΔπαληΞΔύτηÎșΔ σΔ σχέση ΌΔ τÎčς υφÎčÏƒÏ„ÎŹÎŒÎ”ÎœÎ”Ï‚ λύσΔÎčς αÎčÏ‡ÎŒÎźÏ‚ Ï„ÏŒÏƒÎż σΔ Î±Ï…Ï„ÎżÏ„Î”Î»ÎźÏ‚ Î”Ï†Î±ÏÎŒÎżÎłÎ­Ï‚, όπως η ψηφÎčαÎșÎź Î”Ï€Î”ÎŸÎ”ÏÎłÎ±ÏƒÎŻÎ± ÏƒÎźÎŒÎ±Ï„ÎżÏ‚, τα Ï€ÎżÎ»Ï…ÎŒÎ­ÏƒÎ± ÎșαÎč τα Ï€ÏÎżÎČÎ»ÎźÎŒÎ±Ï„Î± αρÎčΞΌητÎčÎșÎźÏ‚ Ï€ÎżÎ»Ï…Ï€Î»ÎżÎșότητας, ÎșαΞώς ÎșαÎč σΔ συστηΌÎčÎșÎŹ Î”Ï„Î”ÏÎżÎłÎ”ÎœÎź πΔρÎčÎČÎŹÎ»Î»ÎżÎœÏ„Î±, όπως έΜα σύστηΌα όρασης Ï…Ï€ÎżÎ»ÎżÎłÎčστώΜ ÎłÎčα Î±Ï…Ï„ÏŒÎœÎżÎŒÎ± ÎŽÎčαστηΌÎčÎșÎŹ ÏÎżÎŒÏ€ÎżÏ„ÎčÎșÎŹ ÎżÏ‡ÎźÎŒÎ±Ï„Î± ÎșαÎč έΜα σύστηΌα Ï€ÎżÎ»Î»Î±Ï€Î»ÏŽÎœ ΔπÎčταχυΜτώΜ υλÎčÎșÎżÏ ÎłÎčα ÏƒÏ„Î±ÎžÎŒÎżÏÏ‚ Î”ÏÎłÎ±ÏƒÎŻÎ±Ï‚ ÎșαÎč ÎșέΜτρα ÎŽÎ”ÎŽÎżÎŒÎ­ÎœÏ‰Îœ, ÏƒÏ„ÎżÏ‡Î”ÏÎżÎœÏ„Î±Ï‚ Î”Ï†Î±ÏÎŒÎżÎłÎ­Ï‚ Ï…ÏˆÎ·Î»ÎźÏ‚ Ï…Ï€ÎżÎ»ÎżÎłÎčστÎčÎșÎźÏ‚ Î±Ï€ÏŒÎŽÎżÏƒÎ·Ï‚ (HPC). ΀α Î±Ï€ÎżÏ„Î”Î»Î­ÏƒÎŒÎ±Ï„Î± ΔΜÎčÏƒÏ‡ÏÎżÏ…Îœ τηΜ Ï€Î”Ï€ÎżÎŻÎžÎ·ÏƒÎ· Ï„ÎżÏ… ÎłÏÎŹÏ†ÎżÎœÏ„Î±, ότÎč η Ï€Î±ÏÎżÏÏƒÎ± ÎŽÎčατρÎčÎČÎź παρέχΔÎč Î±ÎœÏ„Î±ÎłÏ‰ÎœÎčστÎčÎșÎź Ï„Î”Ï‡ÎœÎżÎłÎœÏ‰ÏƒÎŻÎ± ÎłÎčα τηΜ αΜτÎčΌΔτώπÎčση τωΜ Ï€ÎżÎ»ÏÏ€Î»ÎżÎșωΜ ÏƒÏÎłÏ‡ÏÎżÎœÏ‰Îœ ÎșαÎč Ï€ÏÎżÎČλΔπόΌΔΜα ÎŒÎ”Î»Î»ÎżÎœÏ„ÎčÎșώΜ σχΔΎÎčαστÎčÎșώΜ Ï€ÏÎżÎșÎ»ÎźÏƒÎ”Ï‰Îœ

    Design synthesis for dynamically reconfigurable logic systems

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    Dynamic reconfiguration of logic circuits has been a research problem for over four decades. While applications using logic reconfiguration in practical scenarios have been demonstrated, the design of these systems has proved to be a difficult process demanding the skills of an experienced reconfigurable logic design expert. This thesis proposes an automatic synthesis method which relieves designers of some of the difficulties associated with designing partially dynamically reconfigurable systems. A new design abstraction model for reconfigurable systems is proposed in order to support design exploration using the presented method. Given an input behavioural model, a technology server and a set of design constraints, the method will generate a reconfigurable design solution in the form of a 3D floorplan and a configuration schedule. The approach makes use of genetic algorithms. It facilitates global optimisation to accommodate multiple design objectives common in reconfigurable system design, while making realistic estimates of configuration overheads and of the potential for resource sharing between configurations. A set of custom evolutionary operators has been developed to cope with a multiple-objective search space. Furthermore, the application of a simulation technique verifying the lll results of such an automatic exploration is outlined in the thesis. The qualities of the proposed method are evaluated using a set of benchmark designs taking data from a real reconfigurable logic technology. Finally, some extensions to the proposed method and possible research directions are discussed

    A Multi-layer Fpga Framework Supporting Autonomous Runtime Partial Reconfiguration

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    Partial reconfiguration is a unique capability provided by several Field Programmable Gate Array (FPGA) vendors recently, which involves altering part of the programmed design within an SRAM-based FPGA at run-time. In this dissertation, a Multilayer Runtime Reconfiguration Architecture (MRRA) is developed, evaluated, and refined for Autonomous Runtime Partial Reconfiguration of FPGA devices. Under the proposed MRRA paradigm, FPGA configurations can be manipulated at runtime using on-chip resources. Operations are partitioned into Logic, Translation, and Reconfiguration layers along with a standardized set of Application Programming Interfaces (APIs). At each level, resource details are encapsulated and managed for efficiency and portability during operation. An MRRA mapping theory is developed to link the general logic function and area allocation information to the device related physical configuration level data by using mathematical data structure and physical constraints. In certain scenarios, configuration bit stream data can be read and modified directly for fast operations, relying on the use of similar logic functions and common interconnection resources for communication. A corresponding logic control flow is also developed to make the entire process autonomous. Several prototype MRRA systems are developed on a Xilinx Virtex II Pro platform. The Virtex II Pro on-chip PowerPC core and block RAM are employed to manage control operations while multiple physical interfaces establish and supplement autonomous reconfiguration capabilities. Area, speed and power optimization techniques are developed based on the developed Xilinx prototype. Evaluations and analysis of these prototype and techniques are performed on a number of benchmark and hashing algorithm case studies. The results indicate that based on a variety of test benches, up to 70% reduction in the resource utilization, up to 50% improvement in power consumption, and up to 10 times increase in run-time performance are achieved using the developed architecture and approaches compared with Xilinx baseline reconfiguration flow. Finally, a Genetic Algorithm (GA) for a FPGA fault tolerance case study is evaluated as a ultimate high-level application running on this architecture. It demonstrated that this is a hardware and software infrastructure that enables an FPGA to dynamically reconfigure itself efficiently under the control of a soft microprocessor core that is instantiated within the FPGA fabric. Such a system contributes to the observed benefits of intelligent control, fast reconfiguration, and low overhead

    Design and application of reconfigurable circuits and systems

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    AN INVESTIGATION INTO PARTITIONING ALGORITHMS FOR AUTOMATIC HETEROGENEOUS COMPILERS

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    Automatic Heterogeneous Compilers allows blended hardware-software solutions to be explored without the cost of a full-fledged design team, but limited research exists on current partitioning algorithms responsible for separating hardware and software. The purpose of this thesis is to implement various partitioning algorithms onto the same automatic heterogeneous compiler platform to create an apples to apples comparison for AHC partitioning algorithms. Both estimated outcomes and actual outcomes for the solutions generated are studied and scored. The platform used to implement the algorithms is Cal Poly’s own Twill compiler, created by Doug Gallatin last year. Twill’s original partitioning algorithm is chosen along with two other partitioning algorithms: Tabu Search + Simulated Annealing (TSSA) and Genetic Search (GS). These algorithms are implemented inside Twill and test bench input code from the CHStone HLS Benchmark tests is used as stimulus. Along with the algorithms cost models, one key attribute of interest is queue counts generated, as the more cuts between hardware and software requires queues to pass the data between partition crossings. These high communication costs can end up damaging the heterogeneous solution’s performance. The Genetic, TSSA, and Twill’s original partitioning algorithm are all scored against each other’s cost models as well, combining the fitness and performance cost models with queue counts to evaluate each partitioning algorithm. The solutions generated by TSSA are rated as better by both the cost model for the TSSA algorithm and the cost model for the Genetic algorithm while producing low queue counts

    Reconfigurable Instruction Cell Architecture Reconfiguration and Interconnects

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