19 citations · 72 across the 16 of their papers we have counts for
20 papers
A Generalized Optimization Engine (GOE) for Edge AI Inference Acceleration
Venkat R. Dasari, Jakob A. Adams, Vinod K. Mishra +1
Artificial intelligence (AI) models have demonstrated remarkable capabilities across various domains, yet their widespread deployment is impeded by significant computational costs,…
Transferable Latency Prediction for Fast LLM Screening on Heterogeneous Edge Devices
Xiaolong Tu, Vinod K. Mishra, Venkat R. Dasari +2
Accurate latency prediction is critical for deploying large language models (LLMs) on heterogeneous edge devices, where inference latency is affected by model architecture, prompt…
On Accelerating Edge AI: Optimizing Resource-Constrained Environments
Jacob Sander, Achraf Cohen, Venkat R. Dasari +2
Resource-constrained edge deployments demand AI solutions that balance high performance with stringent compute, memory, and energy limitations. In this survey, we present a compreh…
Semantic Edge Computing and Semantic Communications in 6G Networks: A Unifying Survey and Research Challenges
Milin Zhang, Mohammad Abdi, Venkat R. Dasari +1
Semantic Edge Computing (SEC) and Semantic Communications (SemComs) have been proposed as viable approaches to achieve real-time edge-enabled intelligence in sixth-generation (6G)…
Adaptive Stochastic Gradient Descent for Fast and Communication-Efficient Distributed Learning
Serge Kas Hanna, Rawad Bitar, Parimal Parag +2
We consider the setting where a master wants to run a distributed stochastic gradient descent (SGD) algorithm on workers, each having a subset of the data. Distributed SGD may…
Computational complexity reduction of deep neural networks
Mee Seong Im, Venkat R. Dasari
Deep neural networks (DNN) have been widely used and play a major role in the field of computer vision and autonomous navigation. However, these DNNs are computationally complex an…
Virtuoso: Video-based Intelligence for real-time tuning on SOCs
Jayoung Lee, PengCheng Wang, Ran Xu +5
Efficient and adaptive computer vision systems have been proposed to make computer vision tasks, such as image classification and object detection, optimized for embedded or mobile…
ECM: Early Exit via Class Means for Efficient Supervised and Unsupervised Learning
Alperen Görmez, Venkat R. Dasari, Erdem Koyuncu
State-of-the-art neural networks with early exit mechanisms often need considerable amount of training and fine tuning to achieve good performance with low computational cost. We p…
Genetic optimization algorithms applied toward mission computability models
Mee Seong Im, Venkat R. Dasari
Genetic algorithms are modeled after the biological evolutionary processes that use natural selection to select the best species to survive. They are heuristics based and low cost…
Adaptive Distributed Stochastic Gradient Descent for Minimizing Delay in the Presence of Stragglers
Serge Kas Hanna, Rawad Bitar, Parimal Parag +2
We consider the setting where a master wants to run a distributed stochastic gradient descent (SGD) algorithm on workers each having a subset of the data. Distributed SGD may s…
Solving machine learning optimization problems using quantum computers
Venkat R. Dasari, Mee Seong Im, Lubjana Beshaj
Classical optimization algorithms in machine learning often take a long time to compute when applied to a multi-dimensional problem and require a huge amount of CPU and GPU resourc…
Private and Rateless Adaptive Coded Matrix-Vector Multiplication
Rawad Bitar, Yuxuan Xing, Yasaman Keshtkarjahromi +3
Edge computing is emerging as a new paradigm to allow processing data near the edge of the network, where the data is typically generated and collected. This enables critical compu…
Secure Coded Cooperative Computation at the Heterogeneous Edge against Byzantine Attacks
Yasaman Keshtkarjahromi, Rawad Bitar, Venkat Dasari +2
Edge computing is emerging as a new paradigm to allow processing data at the edge of the network, where data is typically generated and collected, by exploiting multiple devices at…
Detecting Network Soft-failures with the Network Link Outlier Factor (NLOF)
Christopher Mendoza, Venkat Dasari, Michael P. McGarry
In this paper, we describe and experimentally evaluate the performance of our Network Link Outlier Factor (NLOF) for detecting soft-failures in communication networks. The NLOF is…
Optimization problems with low SWaP tactical Computing
Mee Seong Im, Venkat R. Dasari, Lubjana Beshaj +1
In a resource-constrained, contested environment, computing resources need to be aware of possible size, weight, and power (SWaP) restrictions. SWaP-aware computational efficiency…
Complexity and mission computability of adaptive computing systems
Venkat R. Dasari, Mee Seong Im, Billy Geerhart
There is a subset of computational problems that are computable in polynomial time for which an existing algorithm may not complete due to a lack of high performance technology on…
Well defined quantum key distribution using calibration, synchronization, and a programmable quantum channel
Billy E. Geerhart, Venkat R. Dasari
Well defined quantum key distribution between two users requires both calibration to ensure quantum effects and synchronization to stabilize the bit parity of the results. Here we…
Optimization and synchronization of programmable quantum communication channels
Mee Seong Im, Venkat R. Dasari
Quantum applications transmit and receive data through quantum and classical communication channels. Channel capacity, the distance and the photon path between transmitting and rec…
Programmable Multi-Node Quantum Network Design and Simulation
Venkat R. Dasari, Ronald J. Sadlier, Ryan Prout +2
Software-defined networking offers a device-agnostic programmable framework to encode new network functions. Externally centralized control plane intelligence allows programmers to…
OpenFlow Arbitrated Programmable Network Channels for Managing Quantum Metadata
Venkat R. Dasari, Travis S. Humble
Quantum networks must classically exchange complex metadata between devices in order to carry out information for protocols such as teleportation, super-dense coding, and quantum k…