Paper 2023/521

TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation

David Bruce Cousins, Duality Technologies
Yuriy Polyakov, Duality Technologies
Ahmad Al Badawi, Duality Technologies
Matthew French, USC, Information Sciences Institute
Andrew Schmidt, USC, Information Sciences Institute
Ajey Jacob, USC, Information Sciences Institute
Benedict Reynwar, USC, Information Sciences Institute
Kellie Canida, USC, Information Sciences Institute
Akhilesh Jaiswal, USC, Information Sciences Institute
Clynn Mathew, USC, Information Sciences Institute
Homer Gamil, New York University
Negar Neda, New York University
Deepraj Soni, New York University
Michail Maniatakos, New York University
Brandon Reagen, New York University
Naifeng Zhang, Carnegie Mellon University
Franz Franchetti, Carnegie Mellon University
Patrick Brinich, Drexel University
Jeremy Johnson, Drexel University
Patrick Broderick, SpiralGen Inc
Mike Franusich, SpiralGen Inc
Bo Zhang, University of Southern California
Zeming Cheng, University of Southern California
Massoud Pedram, University of Southern California

Secure computation is of critical importance to not only the DoD, but across financial institutions, healthcare, and anywhere personally identifiable information (PII) is accessed. Traditional security techniques require data to be decrypted before performing any computation. When processed on untrusted systems the decrypted data is vulnerable to attacks to extract the sensitive information. To address these vulnerabilities Fully Homomorphic Encryption (FHE) keeps the data encrypted during computation and secures the results, even in these untrusted environments. However, FHE requires a significant amount of computation to perform equivalent unencrypted operations. To be useful, FHE must significantly close the computation gap (within 10x) to make encrypted processing practical. To accomplish this ambitious goal the TREBUCHET project is leading research and development in FHE processing hardware to accelerate deep computations on encrypted data, as part of the DARPA MTO Data Privacy for Virtual Environments (DPRIVE) program. We accelerate the major secure standardized FHE schemes (BGV, BFV, CKKS, FHEW, etc.) at >=128-bit security while integrating with the open-source PALISADE and OpenFHE libraries currently used in the DoD and in industry. We utilize a novel tile-based chip design with highly parallel ALUs optimized for vectorized 128b modulo arithmetic. The TREBUCHET coprocessor design provides a highly modular, flexible, and extensible FHE accelerator for easy reconfiguration, deployment, integration and application on other hardware form factors, such as System-on-Chip or alternate chip areas

Note: 6 pages, 5 figures, and 2 tables

Available format(s)
Publication info
Fully Homomorphic EncryptionASICHardware AccelerationBGVBFVCKKSFHEWTFHEDMCGGI
Contact author(s)
dcousins @ dualitytech com
ypolyakov @ dualitytech com
aalbadawi @ dualitytech com
mfrench @ isi edu
aschmidt @ isi edu
ajacob @ isi edu
breynwar @ isi edu
kcanida @ isi edu
akjaiswal @ isi edu
cmathew @ isi edu
homer g @ nyu edu
nn2231 @ nyu edu
dss545 @ nyu edu
michail maniatakos @ nyu edu
bjr5 @ nyu edu
naifengz @ cmu edu
franzf @ cmu edu
pbrinich @ drexel edu
jjohnson @ drexel edu
patrick broderick @ spiralgen com
mike franusich @ spiralgen com
zhangb @ usc edu
chengz @ usc edu
pedram @ usc edu
2023-04-18: last of 2 revisions
2023-04-11: received
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      author = {David Bruce Cousins and Yuriy Polyakov and Ahmad Al Badawi and Matthew French and Andrew Schmidt and Ajey Jacob and Benedict Reynwar and Kellie Canida and Akhilesh Jaiswal and Clynn Mathew and Homer Gamil and Negar Neda and Deepraj Soni and Michail Maniatakos and Brandon Reagen and Naifeng Zhang and Franz Franchetti and Patrick Brinich and Jeremy Johnson and Patrick Broderick and Mike Franusich and Bo Zhang and Zeming Cheng and Massoud Pedram},
      title = {TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation},
      howpublished = {Cryptology ePrint Archive, Paper 2023/521},
      year = {2023},
      note = {\url{}},
      url = {}
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