A comparison and performance evaluation of FPGA soft-cores for embedded multi-core systems

Makni, Mariem; Baklouti, Mouna; Niar, Smaïl; Jmal, Mohamed Wassim; Abid, Mohamed

doi:10.1109/idt.2016.7843032

Cited by 13 publications

(6 citation statements)

References 5 publications

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“…There exist several further survey works comparing multiple RISC-V implementations [29], [37], [34] or processors of different ISAs [17], [32]. However, all are limited to 32 bit variants and target FPGA applications with soft-core processors only.…”

Section: Related Workmentioning

confidence: 99%

A comparative survey of open-source application-class RISC-V processor implementations

Dorflinger

Albers

Kleinbeck

et al. 2021

Proceedings of the 18th ACM International Conference on Computing Frontiers

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The numerous emerging implementations of RISC-V processors and frameworks underline the success of this Instruction Set Architecture (ISA) specification. The free and open source character of many implementations facilitates their adoption in academic and commercial projects. As yet it is not easy to say which implementation fits best for a system with given requirements such as processing performance or power consumption. With varying backgrounds and histories, the developed RISC-V processors are very different from each other. Comparisons are difficult, because results are reported for arbitrary technologies and configuration settings. Scaling factors are used to draw comparisons, but this gives only rough estimates. In order to give more substantiated results, this paper compares the most prominent open-source application-class RISC-V projects by running identical benchmarks on identical platforms with defined configuration settings. The Rocket, BOOM, CVA6, and SHAKTI C-Class implementations are evaluated for processing performance, area and resource utilization, power consumption as well as efficiency. Results are presented for the Xilinx Virtex UltraScale+ family and GlobalFoundries 22FDX ASIC technology. CCS CONCEPTS• Computer systems organization → System on a chip; Serial architectures.

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Section: Related Workmentioning

confidence: 99%

A comparative survey of open-source application-class RISC-V processor implementations

Dorflinger

Albers

Kleinbeck

et al. 2021

Proceedings of the 18th ACM International Conference on Computing Frontiers

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“…Muitos sistemas embarcados utilizam Processadores Soft-Core (PSCs) para viabilizar a implementação em hardware de algoritmos complexos [9]. Dentre os diversos PSCs disponíveis, tanto os comerciais quanto os de código aberto [10], uma característica comum a eles é a sua arquitetura fixa, de forma que, independente da complexidade do programa embarcado, a mesma quantidade de recursos em hardware é alocada. E mais, o tamanho da palavra de dados é fixada geralmente em 32 bits, sendo, na maioria das vezes, superdimensionada.…”

Section: O Processador Saphounclassified

Processamento multicore para reconstrução online de energia por meio de redes neurais

Aguiar¹,

Viccini²,

Ferreira³

et al. 2020

Anais De XXXVIII Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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Resumo-A reconstrução de energia em calorímetros é um processamento executado em pulsos gerados em seus eletrodos para estimar a energia de partículas subatômicas que atravessam seu material. Características não-gaussianas do ruído de calorímetros operando em altas taxas de evento demonstram que métodos não-lineares de estimação são mais indicados. No entanto, tais métodos tendem a ter um alto custo computacional, o que dificulta sua implementação online. Apresenta-se, com este trabalho, a implementação de uma rede neural embarcada em um processamento multicore em FPGA capaz de operar a uma taxa de aquisição acima de 40 MHz, bem como uma implementação no Calorímetro do Experimento ATLAS.

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“…This processor has been chosen for this survey due to its widespread use in harsh environments involving ionizing radiation such as space; LEON3 is one of the processors used by the European space agency [13]. The LEON3 processor is an open-source processor which has performance and efficiency comparable to other well-known soft-core processors while being one of the most configurable soft-core processors [14].…”

Section: The Leon3 Processormentioning

confidence: 99%

Survey of Soft Error Mitigation Techniques Applied to LEON3 Soft Processors on SRAM-Based FPGAs

et al. 2020

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Soft-core processors implemented in SRAM-based FPGAs are an attractive option for applications to be employed in radiation environments due to their flexibility, relatively-low application development costs, and reconfigurability features enabling them to adapt to the evolving mission needs. Despite the advantages soft-core processors possess, they are seldom used in critical applications because they are more sensitive to radiation than their hard-core counterparts. For instance, both the logic and signal routing circuitry of a soft-core processor as well as its user memory are susceptible to radiation-induced faults. Therefore, soft-core processors must be appropriately hardened against ionizing-radiation to become a feasible design choice for harsh environments and thus to reap all their benefits. This survey henceforth discusses various techniques to protect the configuration and user memories of an LEON3 soft processor, which is one of the most widely used soft-core processors in radiation environments, as reported in the stateof-the-art literature, with the objective of facilitating the choice of right fault-mitigation solution for any given soft-core processor.

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A comparison and performance evaluation of FPGA soft-cores for embedded multi-core systems

Cited by 13 publications

References 5 publications

A comparative survey of open-source application-class RISC-V processor implementations

A comparative survey of open-source application-class RISC-V processor implementations

Processamento multicore para reconstrução online de energia por meio de redes neurais

Survey of Soft Error Mitigation Techniques Applied to LEON3 Soft Processors on SRAM-Based FPGAs

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