13 citations · 15 across the 6 of their papers we have counts for
7 papers
LLMs or Naive Bayes? Old Gems or New Ways
Mohammad Firas Sada, Dmitry Mishin, John Graham +3
Large language models (LLMs) prompt a recurring question in research computing: should classical methods like Naive Bayes (NB) be retired? We benchmark Complement Naive Bayes again…
Performance Optimization and Comparative Analysis of Generative AI Models on Advanced Accelerators
Amitash Nanda, Javier Hernandez Nicolau, Madhusudan Gujral +3
Generative AI models, such as Large Language Models (LLMs) and diffusion models, have demonstrated impressive performance across a wide range of tasks. Despite these advances, depl…
The SDSC Satellite Reverse Proxy Service for Launching Secure Jupyter Notebooks on High-Performance Computing Systems
Mary P Thomas, Martin Kandes, James McDougall +4
Using Jupyter notebooks in an HPC environment exposes a system and its users to several security risks. The Satellite Proxy Service, developed at SDSC, addresses many of these secu…
Real-Time In-Network Machine Learning on P4-Programmable FPGA SmartNICs with Fixed-Point Arithmetic and Taylor
Mohammad Firas Sada, John J. Graham, Mahidhar Tatineni +3
As machine learning (ML) applications become integral to modern network operations, there is an increasing demand for network programmability that enables low-latency ML inference…
Serving LLMs in HPC Clusters: A Comparative Study of Qualcomm Cloud AI 100 Ultra and NVIDIA Data Center GPUs
Mohammad Firas Sada, John J. Graham, Elham E Khoda +7
This study presents a benchmarking analysis of the Qualcomm Cloud AI 100 Ultra (QAic) accelerator for large language model (LLM) inference, evaluating its energy efficiency (throug…
The National Research Platform: Stretched, Multi-Tenant, Scientific Kubernetes Cluster
Derek Weitzel, Ashton Graves, Sam Albin +9
The National Research Platform (NRP) represents a distributed, multi-tenant Kubernetes-based cyberinfrastructure designed to facilitate collaborative scientific computing. Spanning…
Towards a Dynamic Composability Approach for using Heterogeneous Systems in Remote Sensing
Ilkay Altintas, Ismael Perez, Dmitry Mishin +8
Influenced by the advances in data and computing, the scientific practice increasingly involves machine learning and artificial intelligence driven methods which requires specializ…