324 citations · 711 across the 34 of their papers we have counts for
34 papers
FPCA: Field-Programmable Pixel Convolutional Array for Extreme-Edge Intelligence
Zihan Yin, Akhilesh Jaiswal
The rapid advancement of neural network applications necessitates hardware that not only accelerates computation but also adapts efficiently to dynamic processing requirements. Whi…
Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural networks: from Algorithms to Technology
Souvik Kundu, Rui-Jie Zhu, Akhilesh Jaiswal +1
Neuromorphic computing and, in particular, spiking neural networks (SNNs) have become an attractive alternative to deep neural networks for a broad range of signal processing appli…
Hardware-Algorithm Co-design Enabling Processing-in-Pixel-in-Memory (P2M) for Neuromorphic Vision Sensors
Md Abdullah-Al Kaiser, Akhilesh R. Jaiswal
The high volume of data transmission between the edge sensor and the cloud processor leads to energy and throughput bottlenecks for resource-constrained edge devices focused on com…
A 9 Transistor SRAM Featuring Array-level XOR Parallelism with Secure Data Toggling Operation
Zihan Yin, Annewsha Datta, Shwetha Vijayakumar +2
Security and energy-efficiency are critical for computing applications in general and for edge applications in particular. Digital in-Memory Computing (IMC) in SRAM cells have wide…
TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation
David Bruce Cousins, Yuriy Polyakov, Ahmad Al Badawi +21
Secure computation is of critical importance to not only the DoD, but across financial institutions, healthcare, and anywhere personally identifiable information (PII) is accessed.…
Object Motion Sensitivity: A Bio-inspired Solution to the Ego-motion Problem for Event-based Cameras
Shay Snyder, Hunter Thompson, Md Abdullah-Al Kaiser +3
Neuromorphic (event-based) image sensors draw inspiration from the human-retina to create an electronic device that can process visual stimuli in a way that closely resembles its b…
Technology-Circuit-Algorithm Tri-Design for Processing-in-Pixel-in-Memory (P2M)
Md Abdullah-Al Kaiser, Gourav Datta, Sreetama Sarkar +6
The massive amounts of data generated by camera sensors motivate data processing inside pixel arrays, i.e., at the extreme-edge. Several critical developments have fueled recent in…
A Context-Switching/Dual-Context ROM Augmented RAM using Standard 8T SRAM
Md Abdullah-Al Kaiser, Edwin Tieu, Ajey P. Jacob +1
The landscape of emerging applications has been continually widening, encompassing various data-intensive applications like artificial intelligence, machine learning, secure encryp…
Neuromorphic-P2M: Processing-in-Pixel-in-Memory Paradigm for Neuromorphic Image Sensors
Md Abdullah-Al Kaiser, Gourav Datta, Zixu Wang +3
Edge devices equipped with computer vision must deal with vast amounts of sensory data with limited computing resources. Hence, researchers have been exploring different energy-eff…
In-Sensor & Neuromorphic Computing are all you need for Energy Efficient Computer Vision
Gourav Datta, Zeyu Liu, Md Abdullah-Al Kaiser +6
Due to the high activation sparsity and use of accumulates (AC) instead of expensive multiply-and-accumulates (MAC), neuromorphic spiking neural networks (SNNs) have emerged as a p…
Enabling ISP-less Low-Power Computer Vision
Gourav Datta, Zeyu Liu, Zihan Yin +3
In order to deploy current computer vision (CV) models on resource-constrained low-power devices, recent works have proposed in-sensor and in-pixel computing approaches that try to…
Performance Modeling Sparse MTTKRP Using Optical Static Random Access Memory on FPGA
Sasindu Wijeratne, Akhilesh Jaiswal, Ajey P. Jacob +2
Electrical static random memory (E-SRAM) is the current standard for internal static memory in Field Programmable Gate Array (FPGA). Despite the dramatic improvement in E-SRAM tech…
IRIS: Integrated Retinal Functionality in Image Sensors
Zihan Yin, Md Abdullah-Al Kaiser, Lamine Ousmane Camara +5
Neuromorphic image sensors draw inspiration from the biological retina to implement visual computations in electronic hardware. Gain control in phototransduction and temporal diffe…
P2M-DeTrack: Processing-in-Pixel-in-Memory for Energy-efficient and Real-Time Multi-Object Detection and Tracking
Gourav Datta, Souvik Kundu, Zihan Yin +11
Today's high resolution, high frame rate cameras in autonomous vehicles generate a large volume of data that needs to be transferred and processed by a downstream processor or mach…
P2M: A Processing-in-Pixel-in-Memory Paradigm for Resource-Constrained TinyML Applications
Gourav Datta, Souvik Kundu, Zihan Yin +5
The demand to process vast amounts of data generated from state-of-the-art high resolution cameras has motivated novel energy-efficient on-device AI solutions. Visual data in such…
Toward Efficient Hyperspectral Image Processing inside Camera Pixels
Gourav Datta, Zihan Yin, Ajey Jacob +2
Hyperspectral cameras generate a large amount of data due to the presence of hundreds of spectral bands as opposed to only three channels (red, green, and blue) in traditional came…
CryoCiM: Cryogenic Compute-in-Memory based on the Quantum Anomalous Hall Effect
Shamiul Alam, Md Mazharul Islam, Md Shafayat Hossain +2
The scaling of the already-matured CMOS technology is steadily approaching its physical limit, motivating the quest for a suitable alternative. Cryogenic operation offers a promisi…
Towards Scalable, Energy-Efficient and Ultra-Fast Optical SRAM
Ramesh Kudalippalliyalil, Sujith Chandran, Ajey P. Jacob +1
Optical static random access memory (O-SRAM) is one of the key components required for achieving the goal of ultra-fast, general-purpose optical computing. We propose and design a…
Augmented Memory Computing: Dynamically Augmented SRAM Storage for Data Intensive Applications
Haripriya Sheshadri, Shwetha Vijayakumar, Ajey Jacob +1
In this paper, we propose a novel memory-centric scheme based on CMOS SRAM for acceleration of data intensive applications. Our proposal aims at dynamically increasing the on-chip…
Intrinsic Spike Timing Dependent Plasticity in Stochastic Magnetic Tunnel Junctions Mediated by Heat Dynamics
Humberto Inzunza Velarde, Jheel Nagaria, Zihan Yin +2
The quest for highly efficient cognitive computing has led to extensive research interest for the field of neuromorphic computing. Neuromorphic computing aims to mimic the behavior…
HYPER-SNN: Towards Energy-efficient Quantized Deep Spiking Neural Networks for Hyperspectral Image Classification
Gourav Datta, Souvik Kundu, Akhilesh R. Jaiswal +1
Hyper spectral images (HSI) provide rich spectral and spatial information across a series of contiguous spectral bands. However, the accurate processing of the spectral and spatial…
IMPULSE: A 65nm Digital Compute-in-Memory Macro with Fused Weights and Membrane Potential for Spike-based Sequential Learning Tasks
Amogh Agrawal, Mustafa Ali, Minsuk Koo +3
The inherent dynamics of the neuron membrane potential in Spiking Neural Networks (SNNs) allows processing of sequential learning tasks, avoiding the complexity of recurrent neural…
IMAC: In-memory multi-bit Multiplication andACcumulation in 6T SRAM Array
Mustafa Ali, Akhilesh Jaiswal, Sangamesh Kodge +3
`In-memory computing' is being widely explored as a novel computing paradigm to mitigate the well known memory bottleneck. This emerging paradigm aims at embedding some aspects of…
Xcel-RAM: Accelerating Binary Neural Networks in High-Throughput SRAM Compute Arrays
Amogh Agrawal, Akhilesh Jaiswal, Deboleena Roy +4
Deep neural networks are a biologically-inspired class of algorithms that have recently demonstrated state-of-the-art accuracies involving large-scale classification and recognitio…