9 citations · 26 across the 14 of their papers we have counts for
15 papers
Count2Multiply: Reliable In-Memory High-Radix Counting
João Paulo Cardoso de Lima, Benjamin Franklin Morris, Asif Ali Khan +2
Computing-in-memory (CIM) has been demonstrated across various memory technologies, ranging from memristive crossbars performing analog dot-product computations to large-scale digi…
CHARM: Composing Heterogeneous Accelerators for Matrix Multiply on Versal ACAP Architecture
Jinming Zhuang, Jason Lau, Hanchen Ye +10
Dense matrix multiply (MM) serves as one of the most heavily used kernels in deep learning applications. To cope with the high computation demands of these applications, heterogene…
Sustainable AI Processing at the Edge
Sébastien Ollivier, Sheng Li, Yue Tang +5
Edge computing is a popular target for accelerating machine learning algorithms supporting mobile devices without requiring the communication latencies to handle them in the cloud.…
A Multi-domain Magneto Tunnel Junction for Racetrack Nanowire Strips
Prayash Dutta, Albert Lee, Kang L. Wang +2
Domain-wall memory (DWM) has SRAM class access performance, low energy, high endurance, high density, and CMOS compatibility. Recently, shift reliability and processing-using-memor…
DNA Pre-alignment Filter using Processing Near Racetrack Memory
Fazal Hameed, Asif Ali Khan, Sebastien Ollivier +2
Recent DNA pre-alignment filter designs employ DRAM for storing the reference genome and its associated meta-data. However, DRAM incurs increasingly high energy consumption backgro…
H2H: Heterogeneous Model to Heterogeneous System Mapping with Computation and Communication Awareness
Xinyi Zhang, Cong Hao, Peipei Zhou +2
The complex nature of real-world problems calls for heterogeneity in both machine learning (ML) models and hardware systems. The heterogeneity in ML models comes from multi-sensor…