TY - GEN
T1 - RPU
T2 - 2023 IEEE International Symposium on Performance Analysis of Systems and Software, ISPASS 2023
AU - Soni, Deepraj
AU - Neda, Negar
AU - Zhang, Naifeng
AU - Reynwar, Benedict
AU - Gamil, Homer
AU - Heyman, Benjamin
AU - Nabeel, Mohammed
AU - Badawi, Ahmad Al
AU - Polyakov, Yuriy
AU - Canida, Kellie
AU - Pedram, Massoud
AU - Maniatakos, Michail
AU - Cousins, David Bruce
AU - Franchetti, Franz
AU - French, Matthew
AU - Schmidt, Andrew
AU - Reagen, Brandon
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Ring-Learning-with-Errors (RLWE) has emerged as the foundation of many important techniques for improving security and privacy, including homomorphic encryption and post-quantum cryptography. While promising, these techniques have received limited use due to their extreme overheads of running on general-purpose machines. In this paper, we present a novel vector Instruction Set Architecture (ISA) and microarchitecture for accelerating the ring-based computations of RLWE. The ISA, named B512, is developed to meet the needs of ring processing workloads while balancing high-performance and general-purpose programming support. Having an ISA rather than fixed hardware facilitates continued software improvement post-fabrication and the ability to support the evolving workloads. We then propose the ring processing unit (RPU), a high-performance, modular implementation of B512. The RPU has native large word modular arithmetic support, capabilities for very wide parallel processing, and a large capacity highbandwidth scratchpad to meet the needs of ring processing. We address the challenges of programming the RPU using a newly developed SPIRAL backend. A configurable simulator is built to characterize design tradeoffs and quantify performance. The best performing design was implemented in RTL and used to validate simulator performance. In addition to our characterization, we show that a RPU using 20.5mm2 of GF12nm can provide a speedup of 1485× over a CPU running a 64k, 128-bit NTT, a core RLWE workload.
AB - Ring-Learning-with-Errors (RLWE) has emerged as the foundation of many important techniques for improving security and privacy, including homomorphic encryption and post-quantum cryptography. While promising, these techniques have received limited use due to their extreme overheads of running on general-purpose machines. In this paper, we present a novel vector Instruction Set Architecture (ISA) and microarchitecture for accelerating the ring-based computations of RLWE. The ISA, named B512, is developed to meet the needs of ring processing workloads while balancing high-performance and general-purpose programming support. Having an ISA rather than fixed hardware facilitates continued software improvement post-fabrication and the ability to support the evolving workloads. We then propose the ring processing unit (RPU), a high-performance, modular implementation of B512. The RPU has native large word modular arithmetic support, capabilities for very wide parallel processing, and a large capacity highbandwidth scratchpad to meet the needs of ring processing. We address the challenges of programming the RPU using a newly developed SPIRAL backend. A configurable simulator is built to characterize design tradeoffs and quantify performance. The best performing design was implemented in RTL and used to validate simulator performance. In addition to our characterization, we show that a RPU using 20.5mm2 of GF12nm can provide a speedup of 1485× over a CPU running a 64k, 128-bit NTT, a core RLWE workload.
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U2 - 10.1109/ISPASS57527.2023.00034
DO - 10.1109/ISPASS57527.2023.00034
M3 - Conference contribution
AN - SCOPUS:85164537397
T3 - Proceedings - 2023 IEEE International Symposium on Performance Analysis of Systems and Software, ISPASS 2023
SP - 272
EP - 282
BT - Proceedings - 2023 IEEE International Symposium on Performance Analysis of Systems and Software, ISPASS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 23 April 2023 through 25 April 2023
ER -