3 citations · 3 across the 3 of their papers we have counts for
7 papers
Exploring the Feasibility of Using 3D XPoint as an In-Memory Computing Accelerator
Masoud Zabihi, Salonik Resch, Husrev Cılasun +5
This paper describes how 3D XPoint memory arrays can be used as in-memory computing accelerators. We first show that thresholded matrix-vector multiplication (TMVM), the fundamenta…
A Machine Learning Accelerator In-Memory for Energy Harvesting
Salonik Resch, S. Karen Khatamifard, Zamshed Iqbal Chowdhury +5
There is increasing demand to bring machine learning capabilities to low power devices. By integrating the computational power of machine learning with the deployment capabilities…
Quantum Computing: An Overview Across the System Stack
Salonik Resch, Ulya R. Karpuzcu
Quantum computers, if fully realized, promise to be a revolutionary technology. As a result, quantum computing has become one of the hottest areas of research in the last few years…
Computational RAM to Accelerate String Matching at Scale
Zamshed I. Chowdhury, S. Karen Khatamifard, Zhengyang Zhao +6
Traditional Von Neumann computing is falling apart in the era of exploding data volumes as the overhead of data transfer becomes forbidding. Instead, it is more energy-efficient to…
PIMBALL: Binary Neural Networks in Spintronic Memory
Salonik Resch, S. Karen Khatamifard, Zamshed Iqbal Chowdhury +5
Neural networks span a wide range of applications of industrial and commercial significance. Binary neural networks (BNN) are particularly effective in trading accuracy for perform…
AISC: Approximate Instruction Set Computer
Alexandra Ferreron, Jesus Alastruey-Benede, Dario Suarez-Gracia +1
This paper makes the case for a single-ISA heterogeneous computing platform, AISC, where each compute engine (be it a core or an accelerator) supports a different subset of the ver…