PERI

Author:

Tiwari Sugandha1,Gala Neel2,Rebeiro Chester1,Kamakoti V.1

Affiliation:

1. Indian Institute of Technology Madras, India

2. InCore Semiconductors Pvt. Ltd., India

Abstract

Owing to the failure of Dennard’s scaling, the past decade has seen a steep growth of prominent new paradigms leveraging opportunities in computer architecture. Two technologies of interest are Posit and RISC-V. Posit was introduced in mid-2017 as a viable alternative to IEEE-754, and RISC-V provides a commercial-grade open source Instruction Set Architecture (ISA). In this article, we bring these two technologies together and propose a Configurable Posit Enabled RISC-V Core called PERI. The article provides insights on how the Single-Precision Floating Point (“F”) extension of RISC-V can be leveraged to support posit arithmetic. We also present the implementation details of a parameterized and feature-complete posit Floating Point Unit (FPU). The configurability and the parameterization features of this unit generate optimal hardware, which caters to the accuracy and energy/area tradeoffs imposed by the applications, a feature not possible with IEEE-754 implementation. The posit FPU has been integrated with the RISC-V compliant SHAKTI C-class core as an execution unit. To further leverage the potential of posit , we enhance our posit FPU to support two different exponent sizes (with posit-size being 32-bits), thereby enabling multiple-precision at runtime. To enable the compilation and execution of C programs on PERI, we have made minimal modifications to the GNU C Compiler (GCC), targeting the “F” extension of the RISC-V. We compare posit with IEEE-754 in terms of hardware area, application accuracy, and runtime. We also present an alternate methodology of integrating the posit FPU with the RISC-V core as an accelerator using the custom opcode space of RISC-V.

Funder

DST-FIST program

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Cited by 21 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Design of a novel low-latency parameterizable posit adder/subtractor using leading one predictor in FPGA;Digital Signal Processing;2024-12

2. Posit and floating-point based Izhikevich neuron: A Comparison of arithmetic;Neurocomputing;2024-09

3. Exploring 8-Bit Arithmetic for Training Spiking Neural Networks;2024 IEEE International Conference on Omni-layer Intelligent Systems (COINS);2024-07-29

4. Big-PERCIVAL: Exploring the Native Use of 64-Bit Posit Arithmetic in Scientific Computing;IEEE Transactions on Computers;2024-06

5. Trading Performance, Power, and Area on Low-Precision Posit MAC Units for CNN Training;2023 IEEE 35th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD);2023-10-17

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