activity
20232026
collaborators

8 papers

cs.DC2026

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…

cs.DC2026

[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…

cs.DC2026

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…

cs.DC2025

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…

cs.CV2025

Scalable Cosmic AI Inference using Cloud Serverless Computing

Mills Staylor, Amirreza Dolatpour Fathkouhi, Md Khairul Islam +4

Large-scale astronomical image data processing and prediction are essential for astronomers, providing crucial insights into celestial objects, the universe's history, and its evol…

cs.DC2024

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…

cs.DC2023

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…

cs.DC2023

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…