5 papers
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…
Decoding Federated Learning: The FedNAM+ Conformal Revolution
Sree Bhargavi Balija, Amitash Nanda, Debashis Sahoo
Federated learning has significantly advanced distributed training of machine learning models across decentralized data sources. However, existing frameworks often lack comprehensi…
Exploring Dynamic Load Balancing Algorithms for Block-Structured Mesh-and-Particle Simulations in AMReX
Amitash Nanda, Md Kamal Hossain Chowdhury, Hannah Ross +1
Load balancing is critical for successful large-scale high-performance computing (HPC) simulations. With modern supercomputers increasing in complexity and variability, dynamic loa…
CPTQuant - A Novel Mixed Precision Post-Training Quantization Techniques for Large Language Models
Amitash Nanda, Sree Bhargavi Balija, Debashis Sahoo
Large language models have transformed the comprehension and generation of natural language tasks, but they come with substantial memory and computational requirements. Quantizatio…
NeuCASL: From Logic Design to System Simulation of Neuromorphic Engines
Dharanidhar Dang, Amitash Nanda, Bill Lin +1
With Moore's law saturating and Dennard scaling hitting its wall, traditional Von Neuman systems cannot offer the GFlops/watt for compute-intensive algorithms such as CNN. Recent t…