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than more coarse-grained architectures due to more elements needing to be addressed and programmed. Therefore, more coarse-grained architectures gain from potential lower energy requirements, as less information is transferred and utilised. Intuitively, the slower the rate of reconfiguration the smaller the power consumption as the associated energy cost of reconfiguration are amortised over a longer period of time. Partial re-configuration aims to allow part of the device to be reprogrammed while another part is still performing active computation. Partial re-configuration allows smaller reconfigurable bit streams thus not wasting energy on transmitting redundant information in the bit stream. Compression of the bit stream is possible but careful analysis is to be carried out to ensure that the energy saved by using smaller bit streams is not outweighed by the computation needed to decompress the data.
719:(ALU), they will perform these computations more quickly and with more power efficiency than a set of interconnected smaller functional units; this is due to the connecting wires being shorter, resulting in less wire capacitance and hence faster and lower power designs. A potential undesirable consequence of having larger computational blocks is that when the size of operands may not match the algorithm an inefficient utilisation of resources can result. Often the type of applications to be run are known in advance allowing the logic, memory and routing resources to be tailored to enhance the performance of the device whilst still providing a certain level of flexibility for future adaptation. Examples of this are domain specific arrays aimed at gaining better performance in terms of power, area, throughput than their more generic finer grained
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the hardware. However, there is a penalty associated with this in terms of increased power, area and delay due to greater quantity of routing required per computation. Fine-grained architectures work at the bit-level manipulation level; whilst coarse grained processing elements (reconfigurable datapath unit, rDPU) are better optimised for standard data path applications. One of the drawbacks of coarse grained architectures are that they tend to lose some of their utilisation and performance if they need to perform smaller computations than their granularity provides, for example for a one bit add on a four bit wide functional unit would waste three bits. This problem can be solved by having a coarse grain array (
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were feasible due to the constant progress of silicon technology that let complex designs be implemented on one chip. Some of these massively parallel reconfigurable computers were built primarily for special subdomains such as molecular evolution, neural or image processing. The world's first commercial reconfigurable computer, the
Algotronix CHS2X4, was completed in 1991. It was not a commercial success, but was promising enough that
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bus to provide a coprocessor like arrangement for the reconfigurable array. However, there have also been implementations where the reconfigurable fabric is much closer to the processor, some are even implemented into the data path, utilising the processor registers. The job of the host processor is to perform the control functions, configure the logic, schedule data and to provide external interfacing.
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371:. A 2008 paper reported speed-up factors of more than 4 orders of magnitude and energy saving factors by up to almost 4 orders of magnitude. Some supercomputer firms offer heterogeneous processing blocks including FPGAs as accelerators. One research area is the twin-paradigm programming tool flow productivity obtained for such heterogeneous systems.
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underlying virtual hardware. This can be relaxed by the concept of threads, allowing different tasks to run concurrently on this virtual hardware to exploit task level parallelism. To allow different processes and threads to coordinate their work, communication and synchronization methods have to be provided by the OS.
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vendors, Xilinx and Altera are the island style layout, where blocks are arranged in an array with vertical and horizontal routing. A layout with inadequate routing may suffer from poor flexibility and resource utilisation, therefore providing limited performance. If too much interconnect is provided
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Often the reconfigurable array is used as a processing accelerator attached to a host processor. The level of coupling determines the type of data transfers, latency, power, throughput and overheads involved when utilising the reconfigurable logic. Some of the most intuitive designs use a peripheral
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Normally, reconfiguring an FPGA requires it to be held in reset while an external controller reloads a design onto it. Partial reconfiguration allows for critical parts of the design to continue operating while a controller either on the FPGA or off of it loads a partial design into a reconfigurable
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In the 1980s and 1990s there was a renaissance in this area of research with many proposed reconfigurable architectures developed in industry and academia, such as: Copacobana, Matrix, GARP, Elixent, NGEN, Polyp, MereGen, PACT XPP, Silicon Hive, Montium, Pleiades, Morphosys, and PiCoGA. Such designs
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The granularity of the reconfigurable logic is defined as the size of the smallest functional unit (configurable logic block, CLB) that is addressed by the mapping tools. High granularity, which can also be known as fine-grained, often implies a greater flexibility when implementing algorithms into
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One of the key challenges for reconfigurable computing is to enable higher design productivity and provide an easier way to use reconfigurable computing systems for users that are unfamiliar with the underlying concepts. One way of doing this is to provide standardization and abstraction, usually
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Configuration of these reconfigurable systems can happen at deployment time, between execution phases or during execution. In a typical reconfigurable system, a bit stream is used to program the device at deployment time. Fine grained systems by their own nature require greater configuration time
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Abstraction is a powerful mechanism to handle complex and different (hardware) tasks in a well-defined and common manner. One of the most elementary OS abstractions is a process. A process is a running application that has the perception (provided by the OS) that it is running on its own on the
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In addition to abstraction, resource management of the underlying hardware components is necessary because the virtual computers provided to the processes and threads by the operating system need to share available physical resources (processors, memory, and devices) spatially and temporarily.
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supports partial reconfiguration of their FPGA devices on 28 nm devices such as
Stratix V, and on the 20 nm Arria 10 devices. The Intel FPGA partial reconfiguration flow for Arria 10 is based on the hierarchical design methodology in the Quartus Prime Pro software where users create
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language to be compiled and executed on FPGA-based computers. The
Mitrion-C software language and Mitrion processor enable software developers to write and execute applications on FPGA-based computers in the same manner as with other computing technologies, such as graphical processing units
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Campi, F.; Toma, M.; Lodi, A.; Cappelli, A.; Canegallo, R.; Guerrieri, R., "A VLIW processor with reconfigurable instruction set for embedded applications", Solid-State
Circuits Conference, 2003. Digest of Technical Papers. ISSCC. 2003 IEEE International, vol., no., pp. 250–491 vol. 1,
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Partial reconfiguration is not supported on all FPGAs. A special software flow with emphasis on modular design is required. Typically the design modules are built along well defined boundaries inside the FPGA that require the design to be specially mapped to the internal hardware.
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One of the major tasks of an operating system is to hide the hardware and present programs (and their programmers) with nice, clean, elegant, and consistent abstractions to work with instead. In other words, the two main tasks of an operating system are abstraction and
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As an emerging field, classifications of reconfigurable architectures are still being developed and refined as new architectures are developed; no unifying taxonomy has been suggested to date. However, several recurring parameters can be used to classify these systems.
126:'s paper proposed the concept of a computer made of a standard processor and an array of "reconfigurable" hardware. The main processor would control the behavior of the reconfigurable hardware. The latter would then be tailored to perform a specific task, such as
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J. M. Arnold and D. A. Buell, "VHDL programming on Splash 2," in More FPGAs, Will Moore and Wayne Luk, editors, Abingdon EE & CS Books, Oxford, England, 1994, pp. 182–191. (Proceedings, International
Workshop on Field-Programmable Logic, Oxford,
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physical partitions of the FPGA that can be reconfigured at runtime while the remainder of the design continues to operate. The
Quartus Prime Pro software also support hierarchical partial reconfiguration and simulation of partial reconfiguration.
300:) migration results in reported speed-up factors of up to more than four orders of magnitude, as well as a reduction in electricity consumption by up to almost four orders of magnitude—although the technological parameters of FPGAs are behind the
523:. It consists of reconfigurable chassis housing the user-programmable FPGA, hot swappable I/O modules, real-time controller for deterministic communication and processing, and graphical LabVIEW software for rapid RT and FPGA programming.
134:, as quickly as a dedicated piece of hardware. Once the task was done, the hardware could be adjusted to do some other task. This resulted in a hybrid computer structure combining the flexibility of software with the speed of hardware.
418:, can be designed modularly, by creating subcomponents and then higher-level components to instantiate them. In many cases it is useful to be able to swap out one or several of these subcomponents while the FPGA is still operating.
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T.J. Todman, G.A. Constantinides, S.J.E. Wilton, O. Mencer, W. Luk and P.Y.K. Cheung, "Reconfigurable
Computing: Architectures and Design Methods", IEEE Proceedings: Computer & Digital Techniques, Vol. 152, No. 2, March 2005,
449:- the device is not active during the reconfiguration process. While the partial data is sent into the FPGA, the rest of the device is stopped (in the shutdown mode) and brought up after the configuration is completed.
146:, FPGA) bought the technology and hired the Algotronix staff. Later machines enabled first demonstrations of scientific principles, such as the spontaneous spatial self-organisation of genetic coding with MereGen.
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or implement more novel architectures. Such projects are built with reconfigurable hardware (FPGAs), and some devices support emulation of multiple vintage computers using a single reconfigurable hardware
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J. M. Arnold, D. A. Buell, D. Hoang, D. V. Pryor, N. Shirazi, M. R. Thistle, "Splash 2 and its applications, "Proceedings, International
Conference on Computer Design, Cambridge, 1993, pp. 482–486.
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McCaskill, John S.; Chorongiewski, Harald; Mekelburg, Karsten; Tangen, Uwe; Gemm, Udo (1994-09-01). "NGEN — Configurable computer hardware to simulate long-time self-organization of biopolymers".
715:) are intended for the implementation for algorithms needing word-width data paths (rDPU). As their functional blocks are optimized for large computations and typically comprise word wide
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The increase of logic in an FPGA has enabled larger and more complex algorithms to be programmed into the FPGA. The attachment of such an FPGA to a modern CPU over a high speed bus, like
106:(ASICs) is the possibility to adapt the hardware during runtime by "loading" a new circuit on the reconfigurable fabric, thus providing new computational blocks without the need to
952:. Sipper, Moshe., Mange, Daniel, 1940-, Pérez-Uribe, Andrés., International Conference on Evolvable Systems (2nd : 1998 : Lausanne, Switzerland). Berlin: Springer. 1998.
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A common example for when partial reconfiguration would be useful is the case of a communication device. If the device is controlling multiple connections, some of which require
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has a center for high-performance reconfigurable computing (CHREC). In April 2011 the fourth Many-core and
Reconfigurable Supercomputing Conference was held in Europe.
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N. Voros, R. Nikolaos, A. Rosti, M. Hübner (editors): Dynamic System
Reconfiguration in Heterogeneous Platforms - The MORPHEUS Approach; Springer Verlag, 2009
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Evolvable systems : from biology to hardware : second International Conference, ICES 98, Lausanne, Switzerland, September 23-25, 1998: proceedings
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Esam El-Araby; Ivan Gonzalez; Tarek El-Ghazawi (January 2009). "Exploiting Partial Runtime Reconfiguration for High-Performance Reconfigurable Computing".
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A. Zomaya (editor): Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies; Springer Verlag, 2006
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by about four orders of magnitude, and the clock frequency is substantially lower than that of microprocessors. This paradox is partly explained by the
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module. Partial reconfiguration also can be used to save space for multiple designs by only storing the partial designs that change between designs.
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A fully FPGA-based computer is the COPACOBANA, the Cost Optimized Codebreaker and Analyzer and its successor RIVYERA. A spin-off company
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combining some of the flexibility of software with the high performance of hardware by processing with flexible hardware platforms like
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of the COPACOBANA-Project of the Universities of Bochum and Kiel in Germany continues the development of fully FPGA-based computers.
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The flexibility in reconfigurable devices mainly comes from their routing interconnect. One style of interconnect made popular by
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is the ability to add custom computational blocks using FPGAs. On the other hand, the main difference from custom hardware, i.e.
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1141:(Munich, Germany). W. Nebel and A. Jerraya, Eds. Design, Automation, and Test in Europe. IEEE Press, Piscataway, NJ, 642–649.
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272:'s following classification scheme of computing paradigms (see "Table 1: Nick Tredennick's Paradigm Classification Scheme").
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systems to be produced where several computational devices can concurrently operate on different data, which is highly
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N. Tredennick: The Case for Reconfigurable Computing; Microprocessor Report, Vol. 10 No. 10, 5 August 1996, pp 25–27.
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Furthermore, by replicating an algorithm on an FPGA or the use of a multiplicity of FPGAs has enabled reconfigurable
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this requires more transistors than necessary and thus more silicon area, longer wires and more power consumption.
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Commercial high-performance reconfigurable computing systems are beginning to emerge with the announcement of
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Estrin, G (2002). "Reconfigurable computer origins: the UCLA fixed-plus-variable (F+V) structure computer".
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is well illustrated by the differences to other machine paradigms that were introduced earlier, as shown by
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Tarek El-Ghazawi; et al. (February 2008). "The promise of high-performance reconfigurable computing".
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Wanta, Damian; Smolik, Waldemar T.; Kryszyn, Jacek; Wróblewski, Przemysław; Midura, Mateusz (2022).
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296:. Hartenstein calls it Reconfigurable Computing Paradox, that software-to-configware (software-to-
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Hauser, John R. and Wawrzynek, John, "Garp: A MIPS Processor with a Reconfigurable Coprocessor",
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that, according to him, represents a fundamental paradigm shift away from the more conventional
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With the advent of affordable FPGA boards, students' and hobbyists' projects seek to recreate
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From the functionality of the design, partial reconfiguration can be divided into two groups:
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The fundamental model of the reconfigurable computing machine paradigm, the data-stream-based
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Estrin, G., "Organization of Computer Systems—The Fixed Plus Variable Structure Computer",
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Hartenstein, R. 2001. A decade of reconfigurable computing: a visionary retrospective. In
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Computer scientist Reiner Hartenstein describes reconfigurable computing in terms of an
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This heterogeneous systems technique is used in computing research and especially in
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Proceedings of the Conference on Design, Automation and Test in Europe (DATE 2001)
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Proceedings of the IEEE Symposium on Field-Programmable Custom Computing Machines
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C. Bobda: Introduction to Reconfigurable Computing: Architectures; Springer, 2007
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D. A. Buell and Kenneth L. Pocek, "Custom computing machines: An introduction,"
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ReCoBus-Builder project for easily implementing complex reconfigurable systems
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The concept of reconfigurable computing has existed since the 1960s, when
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Reconfigurable Computing: The Theory and Practice of FPGA-Based Computing
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Eckert, Marcel; Meyer, Dominik; Haase, Jan; Klauer, Bernd (2016-11-30).
1509:"Quartus Prime Standard Edition Handbook Volume 1: Design and Synthesis"
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1397:"The Design of a RISC Architecture and its Implementation with an FPGA"
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has developed two styles of partial reconfiguration of FPGA devices:
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permits to reconfigure distinct modular parts of the design, while
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98:(FPGAs). The principal difference when compared to using ordinary
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An FPGA board is being used to recreate the Vector-06C computer
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combining reconfigurable computing-based accelerators like
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Creative Commons Attribution 4.0 International (CC BY 4.0)
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1241:"NSF center for High-performance Reconfigurable Computing"
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has developed a SDK that enables software written using a
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ACM Transactions on Reconfigurable Technology and Systems
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have developed a hybrid embedded computing system called
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Table 1: Nick Tredennick's Paradigm Classification Scheme
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Lectures on Reconfigurable Computing at Brown University
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998:. Hoffmann, K.-H. (Karl-Heinz). Berlin: Springer. 2002.
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Berichte der Bunsengesellschaft für Physikalische Chemie
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are often used as a support to partial reconfiguration.
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while the other portion keeps its former configuration.
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Füchslin, Rudolf M.; McCaskill, John S. (2001-07-31).
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can be used when a small change is made to a design.
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317:High-Performance Reconfigurable Computing
75:Learn how and when to remove this message
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155:Tredennick's Classification
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1272:. 2011. Archived from
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1989:Microchip Technology
1794:High-level synthesis
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594:improve this article
517:National Instruments
512:National Instruments
306:Von Neumann syndrome
276:Hartenstein's Xputer
252:Algorithms variable
221:Algorithms variable
2248:Digital electronics
2058:Intel Quartus Prime
1784:Soft microprocessor
1276:on October 12, 2010
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294:von Neumann machine
244:Resources variable
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270:Nick Tredennick
258:(data streams)
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800:iLAND project
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124:Gerald Estrin
117:
115:
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109:
105:
101:
97:
93:
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79:
76:
68:
58:
54:
48:
45:This article
43:
34:
33:
30:
19:
2127:LatticeMico8
2117:ARM Cortex-M
2093:Intellectual
1771:
1617:
1603:
1595:
1549:
1545:
1516:. Retrieved
1503:
1491:. Retrieved
1482:
1470:. Retrieved
1461:
1449:. Retrieved
1440:
1428:. Retrieved
1415:
1403:. Retrieved
1390:
1378:. Retrieved
1369:
1350:
1344:
1325:
1321:
1311:
1300:. Retrieved
1290:
1278:. Retrieved
1274:the original
1269:
1260:
1248:. Retrieved
1244:
1235:
1210:
1206:
1200:
1168:(2): 69–76.
1165:
1161:
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874:
849:
845:
839:
810:One chip MSX
777:
773:
765:
761:
748:
739:
730:
710:
698:
689:
674:
668:January 2015
665:
642:
612:
606:January 2015
603:
592:Please help
587:verification
584:
557:
547:
543:
539:
536:module-based
535:
530:
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499:
487:
470:
446:
440:
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431:
424:
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397:
396:
380:
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366:
355:
336:
319:(HPRC) is a
316:
315:
289:anti-machine
287:
285:
266:anti machine
263:
229:
198:
167:
160:
136:
121:
110:and add new
87:
86:
71:
62:
46:
29:
2157:Open-source
2104:Proprietary
1913:Flow to HDL
1735:Logic block
1518:15 November
1493:15 November
1472:15 November
1451:15 November
1322:Electronics
1213:(4): 1–23.
922:(9): 1114.
695:Granularity
343:coprocessor
339:PCI express
108:manufacture
2237:Categories
2132:MicroBlaze
2083:Simulators
2063:Xilinx ISE
1420:Jan Gray.
1328:(4): 545.
1302:2014-12-14
1280:August 19,
1250:August 19,
852:(4): 3–9.
832:References
652:improve it
521:CompactRIO
501:Mitrionics
496:Mitrionics
484:COPACOBANA
427:encryption
347:peripheral
332:processors
329:multi-core
2202:Microwatt
2197:Libre-SOC
2192:Power ISA
2175:OpenCores
2137:PicoBlaze
1944:Accellera
1937:Companies
1809:Languages
1568:1687-7195
1170:CiteSeerX
1098:0027-8424
1022:cite book
976:cite book
936:0005-9021
815:PipeRench
656:verifying
402:circuitry
2180:OpenRISC
2095:property
2073:ModelSim
2051:Software
2025:Hardware
2018:Products
2004:Synopsys
1974:Infineon
1949:Achronix
1908:C to HDL
1873:Handel-C
1713:Concepts
1581:license.
1552:: 1–11.
1227:10270587
1192:14469864
1116:11470896
1014:49750250
968:39655211
825:Sprinter
783:See also
416:software
353:sphere.
256:Flowware
150:Theories
65:May 2009
2147:Nios II
2037:Stratix
1999:Siemens
1984:Lattice
1969:Cadence
1863:SystemC
1817:Verilog
1610:, 2008.
1076:Bibcode
866:7923912
650:Please
414:, like
374:The US
236:
205:
174:
118:History
51:Please
2209:RISC-V
2068:Vivado
2042:Virtex
1928:Chisel
1893:PALASM
1777:Xputer
1634:1993.)
1566:
1357:
1225:
1190:
1172:
1114:
1104:
1096:
1012:
1002:
966:
956:
934:
864:
805:M-Labs
532:Xilinx
527:Xilinx
282:Xputer
140:Xilinx
1979:Intel
1959:Aldec
1918:MyHDL
1844:VITAL
1512:(PDF)
1430:6 Sep
1425:(PDF)
1405:6 Sep
1400:(PDF)
1380:6 Sep
1223:S2CID
1188:S2CID
1107:55395
862:S2CID
751:FPGAs
559:Intel
554:Intel
478:C-One
216:none
193:none
185:none
112:chips
90:is a
2185:1200
2142:Nios
2122:LEON
1923:ELLA
1903:CUPL
1898:ABEL
1878:Lola
1868:AHDL
1834:VHDL
1767:PSoC
1747:EPLD
1742:CPLD
1730:FPGA
1720:ASIC
1564:ISSN
1550:2016
1520:2016
1495:2016
1474:2016
1453:2016
1432:2012
1407:2012
1382:2012
1355:ISBN
1282:2011
1252:2011
1112:PMID
1094:ISSN
1041:2003
1028:link
1010:OCLC
1000:ISBN
982:link
964:OCLC
954:ISBN
932:ISSN
820:PSoC
721:FPGA
713:rDPA
706:FPGA
538:and
358:SIMD
298:FPGA
2214:Zet
2165:JOP
2112:ARC
2078:VTR
2032:iCE
1994:NXP
1964:Arm
1954:AMD
1888:UPF
1883:PSL
1856:DPI
1839:AMS
1827:AMS
1762:GAL
1757:PAL
1752:PLA
1725:SoC
1554:doi
1330:doi
1215:doi
1180:doi
1102:PMC
1084:doi
924:doi
854:doi
654:by
596:by
480:).
383:IBM
130:or
55:to
2239::
1606:,
1562:.
1548:.
1544:.
1528:^
1326:11
1324:.
1320:.
1268:.
1243:.
1221:.
1209:.
1186:.
1178:.
1166:41
1164:.
1110:.
1100:.
1092:.
1082:.
1072:98
1070:.
1066:.
1024:}}
1020:{{
1008:.
978:}}
974:{{
962:.
930:.
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860:.
850:24
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771:.
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389:.
364:.
334:.
308:.
1822:A
1698:e
1691:t
1684:v
1570:.
1556::
1522:.
1497:.
1476:.
1455:.
1434:.
1409:.
1384:.
1363:.
1338:.
1332::
1305:.
1284:.
1254:.
1229:.
1217::
1211:1
1194:.
1182::
1118:.
1086::
1078::
1030:)
1016:.
984:)
970:.
938:.
926::
868:.
856::
681:)
675:(
670:)
666:(
648:.
619:)
613:(
608:)
604:(
590:.
476:(
78:)
72:(
67:)
63:(
49:.
20:)
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.