Professor Ahmed Louri was awarded a $1.2 Million NSF Grant

Professor Ahmed Louri has been awarded a four-year $1.2 million National Science Foundation grant for the project “Neural-Network-based Stochastic Computing Architectures with applications to Machine Learning,”. Modern computing hardware is constrained by stringent requirements like extremely small size, very low power consumption, and high reliability. Consequently, unconventional computing methods such as Stochastic Computing (SC) that directly address these issues, are of increasing interest, especially for Machine Learning (ML) and Artificial Intelligence (AI) applications. The main attraction of SC is that it enables very low-cost and low-power architectural implementations. This feature is very much relevant to machine learning (ML) as this latter requires significant hardware resources, therefore consuming substantial power when applied to big data. In this research, Prof. Louri and his research team seek to exploit the unique advantages of SC to investigate new architectures and hardware implementations for ML applications. The aim is to develop and design plausible and practical solutions to meet performance, energy and resilience requirements for massive parallelism and fast deployment of hardware to support AI with direct impact on technology and national economic growth. This award brings the total amount of federal funds for Prof. Louri for this research topic to $4 million over the past three years.