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FracTCAM: Fracturable LUTRAM-Based TCAM Emulation on Xilinx FPGAs

FracTCAM: محاكاة TCAM القائمة على لوترام القابلة للكسر على Xilinx FPGAs
Authors: Ali Zahir; Shadan Khattak; Anees Ullah; Pedro Reviriego; Fahad Bin Muslim; Waleed Ahmad;

FracTCAM: Fracturable LUTRAM-Based TCAM Emulation on Xilinx FPGAs

Abstract

En este resumen, presentamos FracTCAM, una metodología eficiente para la emulación de memoria direccionable de contenido ternario (TCAM) en matrices de puertas programables en campo (FPGA) de Xilinx mediante el aprovechamiento de recursos arquitectónicos primitivos. La metodología propuesta aprovecha la naturaleza fracturable de las memorias de acceso aleatorio de tabla de búsqueda (LUTRAM) y los biestables de segmento incorporados para una canalización más profunda. Se pueden combinar múltiples cortes para construir TCAM más profundos y amplios utilizando operaciones and. Esto da como resultado implementaciones de TCAM que logran una menor utilización de recursos, menor retardo y menor consumo de energía. Una comparación con los esquemas existentes muestra que FracTCAM logra consistentemente el mejor rendimiento por área (PA) y el mejor rendimiento por área por vatio (PAW).

Dans ce mémoire, nous présentons FracTCAM, une méthodologie efficace pour l'émulation de mémoire adressable par contenu ternaire (TCAM) sur des réseaux de portes programmables sur site (FPGA) Xilinx en exploitant des ressources architecturales primitives. La méthodologie proposée exploite la nature fracturable des mémoires à accès aléatoire de table de correspondance (LUTRAM) et des bascules de tranche intégrées pour un pipelining plus profond. Plusieurs tranches peuvent être combinées pour construire des TCAM plus profonds et plus larges à l'aide d'opérations ET. Il en résulte des implémentations TCAM qui permettent de réduire l'utilisation des ressources, les retards et la consommation d'énergie. Une comparaison avec les schémas existants montre que FracTCAM atteint systématiquement les meilleures performances par zone (PA) et performances par zone par watt (PAW).

In this brief, we present FracTCAM, an efficient methodology for ternary content addressable memory (TCAM) emulation on Xilinx field-programmable gate arrays (FPGAs) by leveraging primitive architectural resources. The proposed methodology exploits the fracturable nature of lookup table random access memories (LUTRAMs) and built-in slice flip-flops for deeper pipelining. Multiple slices can be combined together to build deeper and wider TCAMs using ANDing operations. This results in TCAM implementations that achieve lower resources utilization, lower delay, and power consumption. A comparison with the existing schemes shows that FracTCAM consistently achieves the best performance per area (PA) and performance per area per watt (PAW).

في هذا الموجز، نقدم FracTCAM، وهي منهجية فعالة لمحاكاة الذاكرة الثلاثية للمحتوى القابل للعنونة (TCAM) على مصفوفات بوابة Xilinx القابلة للبرمجة الميدانية (FPGAs) من خلال الاستفادة من الموارد المعمارية البدائية. تستغل المنهجية المقترحة الطبيعة القابلة للكسر لذكريات الوصول العشوائي لجدول البحث (LUTRAMs) وشباشب الشرائح المدمجة من أجل خطوط أنابيب أعمق. يمكن الجمع بين شرائح متعددة معًا لبناء TCAMs أعمق وأوسع باستخدام عمليات ANDing. وينتج عن ذلك تطبيقات TCAM التي تحقق استخدامًا أقل للموارد وتأخيرًا أقل واستهلاكًا للطاقة. تُظهر المقارنة مع المخططات الحالية أن FracTCAM يحقق باستمرار أفضل أداء لكل منطقة (PA) وأداء لكل منطقة لكل واط (PAW).

Keywords

Parallel computing, Artificial neural network, Computer Networks and Communications, Economics, TCAM Architectures, FLOPS, Dram, Artificial Intelligence, Machine learning, Emulation, Computer architecture, Embedded system, Economic growth, Algorithms and Architectures for Packet Classification, Computer hardware, Lookup table, Computer science, Content-addressable memory, Random access, Field-programmable gate array, Operating system, Hardware and Architecture, Machine Learning for Internet Traffic Classification, Computer Science, Physical Sciences, Network Intrusion Detection and Defense Mechanisms, Content-Addressable Memory

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
Green