1 citations · 1 across the 17 of their papers we have counts for
17 papers
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
Data Management System Analysis for Distributed Computing Workloads
Kuan-Chieh Hsu, Sairam Sri Vatsavai, Ozgur O. Kilic +20
Large-scale international collaborations such as ATLAS rely on globally distributed workflows and data management to process, move, and store vast volumes of data. ATLAS's Producti…
Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
Tasnuva Chowdhury, Tadashi Maeno, Fatih Furkan Akman +23
The collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. R…
Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures
Ozgur O. Kilic, David K. Park, Yihui Ren +18
Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. Thes…
Alternative Mixed Integer Linear Programming Optimization for Joint Job Scheduling and Data Allocation in Grid Computing
Shengyu Feng, Jaehyung Kim, Yiming Yang +18
This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as…
Mixed Delay/Nondelay Embeddings Based Neuromorphic Computing with Patterned Nanomagnet Arrays
Changpeng Ti, Usman Hassan, Sairam Sri Vatsavai +8
Patterned nanomagnet arrays (PNAs) have been shown to exhibit a strong geometrically frustrated dipole interaction. Some PNAs have also shown emergent domain wall dynamics. Previou…
AI Surrogate Model for Distributed Computing Workloads
David K. Park, Yihui Ren, Ozgur O. Kilic +18
Large-scale international scientific collaborations, such as ATLAS, Belle II, CMS, and DUNE, generate vast volumes of data. These experiments necessitate substantial computational…
Scaling Analog Photonic Accelerators for Byte-Size, Integer General Matrix Multiply (GEMM) Kernels
Oluwaseun Adewunmi Alo, Sairam Sri Vatsavai, Ishan Thakkar
Deep Neural Networks (DNNs) predominantly rely on General Matrix Multiply (GEMM) kernels, which are often accelerated using specialized hardware architectures. Recently, analog pho…
A Low-Dissipation and Scalable GEMM Accelerator with Silicon Nitride Photonics
Venkata Sai Praneeth Karempudi, Sairam Sri Vatsavai, Ishan Thakkar +3
Over the past few years, several microring resonator (MRR)-based analog photonic architectures have been proposed to accelerate general matrix-matrix multiplications (GEMMs), which…
A Comparative Analysis of Microrings Based Incoherent Photonic GEMM Accelerators
Sairam Sri Vatsavai, Venkata Sai Praneeth Karempudi, Oluwaseun Adewunmi Alo +1
Several microring resonator (MRR) based analog photonic architectures have been proposed to accelerate general matrix-matrix multiplications (GEMMs) in deep neural networks with ex…
An Optical XNOR-Bitcount Based Accelerator for Efficient Inference of Binary Neural Networks
Sairam Sri Vatsavai, Venkata Sai Praneeth Karempudi, Ishan Thakkar
Binary Neural Networks (BNNs) are increasingly preferred over full-precision Convolutional Neural Networks(CNNs) to reduce the memory and computational requirements of inference pr…
A Bit-Parallel Deterministic Stochastic Multiplier
Sairam Sri Vatsavai, Ishan Thakkar
This paper presents a novel bit-parallel deterministic stochastic multiplier, which improves the area-energy-latency product by up to 10.610, while improving the comput…
SCONNA: A Stochastic Computing Based Optical Accelerator for Ultra-Fast, Energy-Efficient Inference of Integer-Quantized CNNs
Sairam Sri Vatsavai, Venkata Sai Praneeth Karempudi, Ishan Thakkar +2
The acceleration of a CNN inference task uses convolution operations that are typically transformed into vector-dot-product (VDP) operations. Several photonic microring resonators…
AGNI: In-Situ, Iso-Latency Stochastic-to-Binary Number Conversion for In-DRAM Deep Learning
Supreeth Mysore Shivanandamurthy, Sairam Sri Vatsavai, Ishan Thakkar +1
Recent years have seen a rapid increase in research activity in the field of DRAM-based Processing-In-Memory (PIM) accelerators, where the analog computing capability of DRAM is em…
Silicon Photonic Microring Based Chip-Scale Accelerator for Delayed Feedback Reservoir Computing
Sairam Sri Vatsavai, Ishan Thakkar
To perform temporal and sequential machine learning tasks, the use of conventional Recurrent Neural Networks (RNNs) has been dwindling due to the training complexities of RNNs. To…
PROTEUS: Rule-Based Self-Adaptation in Photonic NoCs for Loss-Aware Co-Management of Laser Power and Performance
Sairam Sri Vatsavai, Venkata Sai Praneeth Karempudi, Ishan Thakkar
The performance of on-chip communication in the state-of-the-art multi-core processors that use the traditional electron-ic NoCs has already become severely energy-constrained. To…
Redesigning Photonic Interconnects with Silicon-on-Sapphire Device Platform for Ultra-Low-Energy On-Chip Communication
Venkata Sai Praneeth Karempudi, Sairam Sri Vatsavai, Ishan Thakkar
Traditional silicon-on-insulator (SOI) platform based on-chip photonic interconnects have limited energy-bandwidth scalability due to the optical non-linearity induced power constr…