Dual-Issue Execution of Mixed Integer and Floating-Point Workloads on Energy-Efficient In-Order RISC-V Cores

To meet the computational requirements of modern workloads under tight energy constraints, general-purpose accelerator architectures have to integrate an ever-increasing number of extremely area- and energy-efficient processing elements (PEs). In this context, single-issue in-order cores are commonplace, but lean dual-issue cores could boost PE IPC, especially for the common case of mixed integer and floating-point workloads. We develop the COPIFT methodology and RISC-V ISA extensions to enable low-cost and flexible dual-issue execution of mixed integer and floating-point instruction sequences. On such kernels, our methodology achieves speedups of $1.47 x$, reaching a peak 1.75 instructions per cycle, and 1.37 x energy improvements on average, over optimized RV32G baselines.

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Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1109/dac63849.2025.11132520
Citations
1
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
2.27
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article

Dual-Issue Execution of Mixed Integer and Floating-Point Workloads on Energy-Efficient In-Order RISC-V Cores

Luca Benini, Luca Colagrande
1 citations
Parallel Computing and Optimization Techniques
2.27
article

Dual-Issue Execution of Mixed Integer and Floating-Point Workloads on Energy-Efficient In-Order RISC-V Cores

Luca Benini, Luca Colagrande
article en
1 citations

Abstract

To meet the computational requirements of modern workloads under tight energy constraints, general-purpose accelerator architectures have to integrate an ever-increasing number of extremely area- and energy-efficient processing elements (PEs). In this context, single-issue in-order cores are commonplace, but lean dual-issue cores could boost PE IPC, especially for the common case of mixed integer and floating-point workloads. We develop the COPIFT methodology and RISC-V ISA extensions to enable low-cost and flexible dual-issue execution of mixed integer and floating-point instruction sequences. On such kernels, our methodology achieves speedups of $1.47 x$, reaching a peak 1.75 instructions per cycle, and 1.37 x energy improvements on average, over optimized RV32G baselines.

ETH Zurich (CH)
Openalex Percentile: Top 12%
Parallel Computing and Optimization Techniques
2.27
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