11 papers
OpRAG: A Resource-Deterministic Runtime for GPU-Backed Multi-Stage RAG Workflows
Arup Kumar Sarker, Mills Staylor, Aymen Alsaadi +3
Agentic retrieval-augmented generation (RAG) systems combine preprocessing, embedding, retrieval, memory access, context construction, generation, and vector-index updates. Althoug…
[AAFLOW+] Stateful Operator Abstraction with Zero-Copy Distributed KV Cache Orchestration for Multi-Agent Workflows
Arup Kumar Sarker, Alexander James Halpern, Mills Staylor +5
Multi-agent LLM systems increasingly integrate retrieval, planning, and reasoning, but remain fundamentally text-centric, requiring agents to repeatedly recompute shared context th…
AAFLOW: Scalable Patterns for Agentic AI Workflows
Arup Kumar Sarker, Mills Staylor, Aymen Alsaadi +3
Agentic workflows in large language model systems integrate retrieval, reasoning, and memory, but existing frameworks suffer from scalability and reproducibility limitations due to…
Combining Serverless and High-Performance Computing Paradigms to support ML Data-Intensive Applications
Mills Staylor, Arup Kumar Sarker, Gregor von Laszewski +3
Data is found everywhere, from health and human infrastructure to the surge of sensors and the proliferation of internet-connected devices. To meet this challenge, the data enginee…
Deep RC: A Scalable Data Engineering and Deep Learning Pipeline
Arup Kumar Sarker, Aymen Alsaadi, Alexander James Halpern +7
Significant obstacles exist in scientific domains including genetics, climate modeling, and astronomy due to the management, preprocess, and training on complicated data for deep l…
Design and Implementation of an Analysis Pipeline for Heterogeneous Data
Arup Kumar Sarker, Aymen Alsaadi, Niranda Perera +8
Managing and preparing complex data for deep learning, a prevalent approach in large-scale data science can be challenging. Data transfer for model training also presents difficult…
In-depth Analysis On Parallel Processing Patterns for High-Performance Dataframes
Niranda Perera, Arup Kumar Sarker, Mills Staylor +7
The Data Science domain has expanded monumentally in both research and industry communities during the past decade, predominantly owing to the Big Data revolution. Artificial Intel…
PCV: A Point Cloud-Based Network Verifier
Arup Kumar Sarker, Farzana Yasmin Ahmad, Matthew B. Dwyer
3D vision with real-time LiDAR-based point cloud data became a vital part of autonomous system research, especially perception and prediction modules use for object classification,…
Supercharging Distributed Computing Environments For High Performance Data Engineering
Niranda Perera, Kaiying Shan, Supun Kamburugamuwe +7
The data engineering and data science community has embraced the idea of using Python & R dataframes for regular applications. Driven by the big data revolution and artificial inte…
MVAM: Multi-variant Attacks on Memory for IoT Trust Computing
Arup Kumar Sarker, Md Khairul Islam, Yuan Tian
With the significant development of the Internet of Things and low-cost cloud services, the sensory and data processing requirements of IoT systems are continually going up. TrustZ…
Hybrid Cloud and HPC Approach to High-Performance Dataframes
Kaiying Shan, Niranda Perera, Damitha Lenadora +6
Data pre-processing is a fundamental component in any data-driven application. With the increasing complexity of data processing operations and volume of data, Cylon, a distributed…