Tendayi Kamucheka Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

University of Arkansas at Fayetteville

faculty

2 h-index 10 pubs 40 cited

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Biography and Research Information

OverviewAI-generated summary

Tendayi Kamucheka's research focuses on the design and implementation of hardware accelerators for computational tasks. His work includes the development of in-memory computing engines, such as IMAGine, which accelerates matrix-vector multiplication, and DA-VinCi, a deep-learning accelerator overlay. Kamucheka has also investigated hardware security, including masked implementations of cryptographic algorithms like Kyber and power-based side-channel attack analysis on post-quantum cryptography (PQC) algorithms. His publications explore compiler-driven approaches for hardware/software co-design of deep-learning accelerators and the optimization of accelerators using BRAM (Block RAM) resources. Kamucheka collaborates with researchers at the University of Arkansas at Fayetteville, including Miaoqing Huang and David Andrews, with whom he has co-authored multiple publications.

Metrics

  • h-index: 2
  • Publications: 10
  • Citations: 40

Selected Publications

  • DA-VinCi: A Deep-Learning Accelerator Overlay Using In-Memory Computing (2025) DOI
  • IMAGine: An In-Memory Accelerated GEMV Engine Overlay (2024) DOI
  • The BRAM is the Limit: Shattering Myths, Shaping Standards, and Building Scalable PIM Accelerators (2024) DOI
  • Ph.D. Project: A Compiler-Driven Approach to HW/SW Co-Design of Deep-Learning Accelerators (2024) DOI
  • A Masked Pure-Hardware Implementation of Kyber Cryptographic Algorithm (2022) DOI

Collaborators

Researchers in the database who share publications