Research Areas
Biography and Research Information
OverviewAI-generated summary
Nathaniel Fredricks' research focuses on the design and implementation of hardware accelerators for computing tasks, particularly those involving in-memory computing. His work aims to improve the efficiency and performance of these systems. Fredricks has co-authored publications on topics such as "IMAGine: An In-Memory Accelerated GEMV Engine Overlay," which details a specific hardware overlay for matrix operations, and "DA-VinCi: A Deep-Learning Accelerator Overlay Using In-Memory Computing," exploring the application of in-memory computing for deep learning workloads. He also investigates the physical limitations and design standards for scalable processing-in-memory (PIM) accelerators, as highlighted in "The BRAM is the Limit: Shattering Myths, Shaping Standards, and Building Scalable PIM Accelerators." Fredricks collaborates with researchers David Andrews, Tendayi Kamucheka, and Miaoqing Huang at the University of Arkansas at Fayetteville, with whom he shares multiple publications.
Metrics
- h-index: 1
- Publications: 4
- Citations: 6
Selected Publications
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DA-VinCi: A Deep-Learning Accelerator Overlay Using In-Memory Computing (2025)
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IMAGine: An In-Memory Accelerated GEMV Engine Overlay (2024)
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The BRAM is the Limit: Shattering Myths, Shaping Standards, and Building Scalable PIM Accelerators (2024)
Collaboration Network
Top Collaborators
- IMAGine: An In-Memory Accelerated GEMV Engine Overlay
- The BRAM is the Limit: Shattering Myths, Shaping Standards, and Building Scalable PIM Accelerators
- DA-VinCi: A Deep-Learning Accelerator Overlay Using In-Memory Computing
- IMAGine: An In-Memory Accelerated GEMV Engine Overlay
- The BRAM is the Limit: Shattering Myths, Shaping Standards, and Building Scalable PIM Accelerators
- DA-VinCi: A Deep-Learning Accelerator Overlay Using In-Memory Computing
- IMAGine: An In-Memory Accelerated GEMV Engine Overlay
- The BRAM is the Limit: Shattering Myths, Shaping Standards, and Building Scalable PIM Accelerators
- DA-VinCi: A Deep-Learning Accelerator Overlay Using In-Memory Computing
- IMAGine: An In-Memory Accelerated GEMV Engine Overlay
- The BRAM is the Limit: Shattering Myths, Shaping Standards, and Building Scalable PIM Accelerators
- DA-VinCi: A Deep-Learning Accelerator Overlay Using In-Memory Computing
- IMAGine: An In-Memory Accelerated GEMV Engine Overlay
- The BRAM is the Limit: Shattering Myths, Shaping Standards, and Building Scalable PIM Accelerators
- IMAGine: An In-Memory Accelerated GEMV Engine Overlay
- The BRAM is the Limit: Shattering Myths, Shaping Standards, and Building Scalable PIM Accelerators
- DA-VinCi: A Deep-Learning Accelerator Overlay Using In-Memory Computing
- DA-VinCi: A Deep-Learning Accelerator Overlay Using In-Memory Computing
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