49 citations · 125 across the 28 of their papers we have counts for
31 papers
Vision-Language Models Integrate Conflicting Evidence Like Biased Bayesian Observers
Josh Barua, Kyle Mahowald, William Rudman
Vision-language models must reconcile conflicting text and images. Prior work has characterized the resulting behavior in terms of modality biases--e.g., a "blind faith in text"--b…
PRIM: Energy- and Endurance-Aware Compiler Optimization for Digital Compute in Non-volatile Memory
Patrick Miller, Ulya R. Karpuzcu
Compute-in-Memory (CiM) is an alternative computing paradigm that circumvents the memory bandwidth bottleneck. Variants utilizing non-volatile memory cells (NVCiM) to perform Boole…
Ising Acceleration for Multi-Robot Multi-Target Planning
Ahmet Efe, Recep B. Uludag, Chris H. Kim +1
Ising machines are emerging as promising hardware for combinatorial optimization. With recent advances in CMOS Ising technology, they are becoming attractive as low-power accelerat…
Breaking Local-Minimum Traps in Spiking Neural Network-Based Solvers for CSPs via Parallel Tempering
Recep Bugra Uludag, Ahmet Efe, Ismail Akturk +1
Spiking neural networks (SNNs) with stochastic neurons can solve constraint satisfaction problems (CSPs) by encoding constraints via connectivity and performing probabilistic searc…
Computing In Spintronic Memory: A Thermal Perspective
Patrick Miller, Hüsrev Cilasun, Sachin S. Sapatnekar +1
Computing-in-Memory (CiM) is a promising paradigm to address the memory bottleneck constraining traditional systems. Most power-efficient CiM variants can directly perform Boolean…
Implicitly Parallel Neuromorphic Solver Design for Constraint Satisfaction Problems
Recep Bugra Uludag, Ahmet Efe, Ismail Akturk +1
Many real-life problems of practical importance -- spanning a wide range of applications from chip design to bioinformatics -- represent constraint satisfaction problems, where cla…
An FPGA-ASIC Co-Design Framework for Capacity-Constrained Physics-Based Ising Chips
Ruihong Yin, Yue Zheng, Chaohui Li +6
When a problem exceeds an analog Ising machine's spin capacity it cannot be solved in one shot: a digital orchestration layer must iteratively decompose the graph, clamp boundary s…
Extractive summarization on a CMOS Ising machine
Ziqing Zeng, Abhimanyu Kumar, Ahmet Efe +4
Extractive summarization (ES) aims to generate a concise summary by selecting a subset of sentences from a document while maximizing relevance and minimizing redundancy. Although m…
On the Limits of Ising Machines for Circuit-Derived SAT
Ahmet Efe, Hüsrev Cılasun, Abhimanyu Kumar +9
Emerging Ising machines are promising for solving computationally hard optimization problems, yet their limits on structured, circuit-derived satisfiability (SAT) problems remain p…
Supporting Higher-Order Interactions in Practical Ising Machines
Nafisa Sadaf Prova, Hüsrev Cılasun, Abhimanyu Kumar +3
Ising machines as hardware solvers of combinatorial optimization problems (COPs) can efficiently explore large solution spaces due to their inherent parallelism and physics-based d…
DROID: Discrete-Time Simulation for Ring-Oscillator-Based Ising Design
Abhimanyu Kumar, Ramprasath S., Chris H. Kim +2
Many combinatorial problems can be mapped to Ising machines, i.e., networks of coupled oscillators that settle to a minimum-energy ground state, from which the problem solution is…
HETRI: Heterogeneous Ising Multiprocessing
Ahmet Efe, Hüsrev Cılasun, Abhimanyu Kumar +4
Ising machines are effective solvers for complex combinatorial optimization problems. The idea is mapping the optimal solution(s) to a combinatorial optimization problem to the min…
Experimental demonstration of magnetic tunnel junction-based computational random-access memory
Yang Lv, Brandon R. Zink, Robert P. Bloom +9
Conventional computing paradigm struggles to fulfill the rapidly growing demands from emerging applications, especially those for machine intelligence, because much of the power an…
3SAT on an All-to-All-Connected CMOS Ising Solver Chip
Hüsrev Cılasun, Ziqing Zeng, Ramprasath S +6
This work solves 3SAT, a classical NP-complete problem, on a CMOS-based Ising hardware chip with all-to-all connectivity. The paper addresses practical issues in going from algorit…
On Error Correction for Nonvolatile Processing-In-Memory
Hüsrev Cılasun, Salonik Resch, Zamshed I. Chowdhury +6
Processing in memory (PiM) represents a promising computing paradigm to enhance performance of numerous data-intensive applications. Variants performing computing directly in emerg…
Towards Homomorphic Inference Beyond the Edge
Salonik Resch, Zamshed I. Chowdhury, Husrev Cilasun +5
Beyond edge devices can function off the power grid and without batteries, enabling them to operate in difficult to access regions. However, energy costly long-distance communicati…
Effectiveness of Variable Distance Quantum Error Correcting Codes
Salonik Resch, Ulya R. Karpuzcu
Quantum error correction is capable of digitizing quantum noise and increasing the robustness of qubits. Typically, error correction is designed with the target of eliminating all…
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…
On Value Recomputation to Accelerate Invisible Speculation
Christos Sakalis, Zamshed I. Chowdhury, Shayne Wadle +5
Recent architectural approaches that address speculative side-channel attacks aim to prevent software from exposing the microarchitectural state changes of transient execution. The…
An Inference and Learning Engine for Spiking Neural Networks in Computational RAM (CRAM)
Hüsrev Cılasun, Salonik Resch, Zamshed I. Chowdhury +8
Spiking Neural Networks (SNN) represent a biologically inspired computation model capable of emulating neural computation in human brain and brain-like structures. The main promise…
Benchmarking Quantum Computers and the Impact of Quantum Noise
Salonik Resch, Ulya R. Karpuzcu
Benchmarking is how the performance of a computing system is determined. Surprisingly, even for classical computers this is not a straightforward process. One must choose the appro…
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…