High Performance Instruction Fetch Structure within a RISC-V Processor for Use in Harsh Environments

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Original languageEnglish
Title of host publicationLecture Notes in Computer Science
Subtitle of host publicationEmbedded Computer Systems: Architectures, Modeling, and Simulation 23rd International Conference, SAMOS 2023 Samos, Greece, July 2–6, 2023 Proceedings
EditorsCristina Silvano, Marc Reichenbach, Christian Pilato
ChapterOpen Hardware RISC-V Technologies
Pages255-268
Number of pages14
Volume23
ISBN (electronic)978-3-031-46077-7
Publication statusPublished - 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14385 LNCS
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Abstract

An increasing number of sensors and actuators are being
used in today’s high-tech drilling tools to further optimise the drilling
process. Each sensor and actuator either generates data that needs to
be processed or requires real-time input control signals. RISC-V proces-
sors are being developed to meet the computational demands of today’s
harsh environment applications. A known bottleneck for processors is
the data flow and instruction input to the processor, especially as mem-
ory response times are particularly high for the state-of-the-art 180 nm
harsh environment silicon-on-insulator (SOI) technology, further limit-
ing the design space. Therefore, this paper presents a high-performance
instruction fetch architecture that achieves a high clock frequency while
preserving high instructions per cycle. We evaluate different approaches
to implementing such a design and propose a design that is able to reach
up to 0.73 instructions per cycle (IPC) and achieve a clock frequency of
229 MHz, which is more than twice as high as previous designs in this
technology. The new architecture achieves 167 million instructions per
second (MIPS), which is four times higher than the rocket chip achieves
when synthesised for the same harsh environment technology.

Keywords

    RISC-V, Instruction Fetch, Cache, Harsh environment, ASIC, Synthesis, ASIC Synthesis, Harsh Environment

ASJC Scopus subject areas

Research Area (based on ÖFOS 2012)

  • TECHNICAL SCIENCES
  • Electrical Engineering, Electronics, Information Engineering
  • Electrical Engineering, Electronics, Information Engineering
  • Computer architecture

Cite this

High Performance Instruction Fetch Structure within a RISC-V Processor for Use in Harsh Environments. / Hawich, Malte; Rumpeltin, Nico (Contributor); Rücker, Malte (Contributor) et al.
Lecture Notes in Computer Science: Embedded Computer Systems: Architectures, Modeling, and Simulation 23rd International Conference, SAMOS 2023 Samos, Greece, July 2–6, 2023 Proceedings. ed. / Cristina Silvano; Marc Reichenbach; Christian Pilato. Vol. 23 2023. p. 255-268 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14385 LNCS).

Research output: Chapter in book/report/conference proceedingContribution to book/anthologyResearchpeer review

Hawich, M, Rumpeltin, N, Rücker, M, Stuckenberg, T & Blume, H 2023, High Performance Instruction Fetch Structure within a RISC-V Processor for Use in Harsh Environments. in C Silvano, M Reichenbach & C Pilato (eds), Lecture Notes in Computer Science: Embedded Computer Systems: Architectures, Modeling, and Simulation 23rd International Conference, SAMOS 2023 Samos, Greece, July 2–6, 2023 Proceedings. vol. 23, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14385 LNCS, pp. 255-268. https://doi.org/10.1007/978-3-031-46077-7_17
Hawich, M., Rumpeltin, N., Rücker, M., Stuckenberg, T., & Blume, H. (2023). High Performance Instruction Fetch Structure within a RISC-V Processor for Use in Harsh Environments. In C. Silvano, M. Reichenbach, & C. Pilato (Eds.), Lecture Notes in Computer Science: Embedded Computer Systems: Architectures, Modeling, and Simulation 23rd International Conference, SAMOS 2023 Samos, Greece, July 2–6, 2023 Proceedings (Vol. 23, pp. 255-268). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14385 LNCS). https://doi.org/10.1007/978-3-031-46077-7_17
Hawich M, Rumpeltin N, Rücker M, Stuckenberg T, Blume H. High Performance Instruction Fetch Structure within a RISC-V Processor for Use in Harsh Environments. In Silvano C, Reichenbach M, Pilato C, editors, Lecture Notes in Computer Science: Embedded Computer Systems: Architectures, Modeling, and Simulation 23rd International Conference, SAMOS 2023 Samos, Greece, July 2–6, 2023 Proceedings. Vol. 23. 2023. p. 255-268. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2023 Nov 7. doi: 10.1007/978-3-031-46077-7_17
Hawich, Malte ; Rumpeltin, Nico ; Rücker, Malte et al. / High Performance Instruction Fetch Structure within a RISC-V Processor for Use in Harsh Environments. Lecture Notes in Computer Science: Embedded Computer Systems: Architectures, Modeling, and Simulation 23rd International Conference, SAMOS 2023 Samos, Greece, July 2–6, 2023 Proceedings. editor / Cristina Silvano ; Marc Reichenbach ; Christian Pilato. Vol. 23 2023. pp. 255-268 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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