5 papers
NDS: Programmer-Free Offload of High-Performance Near Data Strands
Shreyas Singh, Pratyush Nandi, Lin Jia +2
Near Data Processing (NDP) has the potential to significantly improve system performance and energy by alleviating data movement bottlenecks. However, most NDP proposals pose heavy…
BEACON: A Versatile Accelerator for Computational Pathology Applications
Sumanth Gudaparthi, Ananth Krishna Prasad, Lin Jia +2
While accelerators for AI have seen great commercial success, it is challenging to replicate that success for other specialized domains due to a number of factors. We make the case…
Towards Enabling Distance-Based Memory Addressing
Ananth Krishna Prasad, Rajeev Balasubramonian, Sharad Bhat +1
Approximate Nearest-Neighbor Search (ANNS) in high dimensional vector datasets is an application of significant prevalence across different AI applications. However, such an operat…
XCRYPT: Accelerating Lattice Based Cryptography with Memristor Crossbar Arrays
Sarabjeet Singh, Xiong Fan, Ananth Krishna Prasad +5
This paper makes a case for accelerating lattice-based post quantum cryptography (PQC) with memristor based crossbars, and shows that these inherently error-tolerant algorithms are…
Newton: Gravitating Towards the Physical Limits of Crossbar Acceleration
Anirban Nag, Ali Shafiee, Rajeev Balasubramonian +2
Many recent works have designed accelerators for Convolutional Neural Networks (CNNs). While digital accelerators have relied on near data processing, analog accelerators have furt…