13 citations · 31 across the 17 of their papers we have counts for
6 papers · 1 filter
TDPP: Two-Dimensional Permutation-Based Protection of Memristive Deep Neural Networks
Minhui Zou, Zhenhua Zhu, Tzofnat Greenberg-Toledo +6
The execution of deep neural network (DNN) algorithms suffers from significant bottlenecks due to the separation of the processing and memory units in traditional computer systems.…
PyPIM: Integrating Digital Processing-in-Memory from Microarchitectural Design to Python Tensors
Orian Leitersdorf, Ronny Ronen, Shahar Kvatinsky
Digital processing-in-memory (PIM) architectures mitigate the memory wall problem by facilitating parallel bitwise operations directly within the memory. Recent works have demonstr…
Performance Analysis of Digital Processing-in-Memory through a Case Study on Convolutional-Neural-Network Acceleration
Orian Leitersdorf, Ronny Ronen, Shahar Kvatinsky
Processing-in-Memory (PIM) architectures are evolving to minimize data movement by leveraging the same physical devices for both memory and logic functionalities. While analog PIM…
FourierPIM: High-Throughput In-Memory Fast Fourier Transform and Polynomial Multiplication
Orian Leitersdorf, Yahav Boneh, Gonen Gazit +2
The Discrete Fourier Transform (DFT) is essential for various applications ranging from signal processing to convolution and polynomial multiplication. The groundbreaking Fast Four…
Universal Framework for Parametric Constrained Coding
Daniella Bar-Lev, Adir Kobovich, Orian Leitersdorf +1
Constrained coding is a fundamental field in coding theory that tackles efficient communication through constrained channels. While channels with fixed constraints have a general o…
ClaPIM: Scalable Sequence CLAssification using Processing-In-Memory
Marcel Khalifa, Barak Hoffer, Orian Leitersdorf +4
DNA sequence classification is a fundamental task in computational biology with vast implications for applications such as disease prevention and drug design. Therefore, fast high-…