TY - GEN
T1 - Efficient organization of digital periphery to support integer datatype for memristor-based cim
AU - Zahedi, Mahdi
AU - Mayahinia, Mahta
AU - Abu Lebdeh, Muath
AU - Wong, Stephan
AU - Hamdioui, Said
N1 - Accepted author manuscript
PY - 2020
Y1 - 2020
N2 - Von Neumann-based architectures suffer from costly communication between CPU and memory. This communication imposes several orders of magnitude more power and performance overheads compared to the arithmetic operations performed by the processor. This overhead becomes critical for applications that require processing a large amount of data. Computation-in-Memory (CIM) leveraging memristor devices in the crossbar structure offers a potential solution to tackle this challenge. However, support for the integer data type is lacking in CIM approaches as most solutions operate on a single/few bits only. This paper proposes a new organization of the periphery (next to memristor crossbar) to compute matrix-matrix multiplication (MMM) at the tile level. More precisely, the analog additions performed in the crossbar is complemented with additions performed in the digital periphery. In this mixed analog-digital system, digital additions are performed in a way that only the minimum size of adders are required-this is to reduce the latency of the digital periphery as much as possible. In addition, the design is customized to the number of ADCs as well as datatype sizes to support different possible scenarios. The results show that our organization reduces energy and latency up to 50x and 3x, respectively, compared to the reference design.
AB - Von Neumann-based architectures suffer from costly communication between CPU and memory. This communication imposes several orders of magnitude more power and performance overheads compared to the arithmetic operations performed by the processor. This overhead becomes critical for applications that require processing a large amount of data. Computation-in-Memory (CIM) leveraging memristor devices in the crossbar structure offers a potential solution to tackle this challenge. However, support for the integer data type is lacking in CIM approaches as most solutions operate on a single/few bits only. This paper proposes a new organization of the periphery (next to memristor crossbar) to compute matrix-matrix multiplication (MMM) at the tile level. More precisely, the analog additions performed in the crossbar is complemented with additions performed in the digital periphery. In this mixed analog-digital system, digital additions are performed in a way that only the minimum size of adders are required-this is to reduce the latency of the digital periphery as much as possible. In addition, the design is customized to the number of ADCs as well as datatype sizes to support different possible scenarios. The results show that our organization reduces energy and latency up to 50x and 3x, respectively, compared to the reference design.
UR - http://www.scopus.com/inward/record.url?scp=85090407927&partnerID=8YFLogxK
U2 - 10.1109/ISVLSI49217.2020.00047
DO - 10.1109/ISVLSI49217.2020.00047
M3 - Conference contribution
AN - SCOPUS:85090407927
SN - 978-1-7281-5776-4
T3 - 2020 IEEE COMPUTER SOCIETY ANNUAL SYMPOSIUM ON VLSI (ISVLSI 2020)
SP - 216
EP - 221
BT - 2020 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)
A2 - O'Conner, L.
PB - IEEE
CY - Piscataway
T2 - 19th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2020
Y2 - 6 July 2020 through 8 July 2020
ER -