CRAFFT: High Resolution FFT Accelerator In Spintronic Computational RAM
M. Hüsrev Cilasun, Salonik Resch, Zamshed Iqbal Chowdhury, Erin Olson, Masoud Zabihi, Zhengyang Zhao, Thomas Peterson, Jianping Wang, Sachin S. Sapatnekar, Ulya R. Karpuzcu
Abstract
High resolution Fast Fourier Transform (FFT) is important for various applications while increased memory access and parallelism requirement limits the traditional hardware. In this work, we explore acceleration opportunities for high resolution FFTs in spintronic computational RAM (CRAM) which supports true in-memory processing semantics. We experiment with Spin-Torque-Transfer (STT) and Spin-Hall-Effect (SHE) based CRAMs in implementing CRAFFT, a high resolution FFT accelerator in memory. For one million point fixed-point FFT, we demonstrate that CRAFFT can provide up to 2.57× speedup and 673× energy reduction. We also provide a proof-of-concept extension to floating-point FFT.
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Install the CLIlune papers fulltext accadc18-5957-41ed-8e35-2c7f77f9c2dcCited by top-tier papers4
- MOUSE: Inference In Non-volatile Memory for Energy Harvesting ApplicationsSalonik Resch, S. Karen Khatamifard, Zamshed I. Chowdhury, Masoud Zabihi et al.MICRO 2020 · 37 citations
- On Endurance of Processing in (Nonvolatile) MemorySalonik Resch, M. Hüsrev Cilasun, Zamshed I. Chowdhury, Masoud Zabihi et al.ISCA 2023 · 15 citations
- Bind the gap: compiling real software to hardware FFT acceleratorsJackson Woodruff, Jordi Armengol-Estapé, Sam Ainsworth, Michael F. P. O'BoylePLDI 2022 · 14 citations
- On Error Correction for Nonvolatile Processing-In-MemoryHüsrev Cilasun, Salonik Resch, Zamshed I. Chowdhury, Masoud Zabihi et al.ISCA 2024 · 11 citations
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