High Performance Computing

High Performance Computing (HPC) integrates high end hardware with highly tuned software to solve complex scientific problems. HPC simplifies and accelerates substantial computational components in a number of essential fields, such as genome sequencing and molecular dynamics in computational biology or cyber physical domains. HPC also applies data driven and AI techniques to diagnose and solve performance challenges in HPC systems themselves. HPC research at CISE focuses on improving performance, reducing cost, and making the systems more energy efficient by applying intelligent and interdisciplinary methods. Research areas cross-cut design automation (EDA), computer architecture, computer systems, and applied machine learning.

Balancing electricity demands and costs of high-performance computing

Some computational problems are so complex that they require many times more calculations than a typical laptop can handle. High performance computing (HPC) combines a number of computer servers to carry out these large-scale computations that often operate on massive data sets. But data centers for HPC require immense amounts of power and limiting power […]

Automated Analytics for Improving Efficiency, Safety, and Security of HPC Systems

Performance variations are becoming more prominent with new generations of large-scale High Performance Computing (HPC) systems. Understanding these variations and developing resilience to anomalous performance behavior are critical challenges for reaching extreme-scale computing. To help address these emerging performance variation challenges, there is increasing interest in designing data analytics methods to make sense out of the […]

AI-based Scalable Analytics for Improving Performance, Resilience, and Security of HPC Systems

Next generation large-scale  High Performance Computing (HPC) systems face important cost and scalability challenges due to anomalous system and application behavior resulting in wasted compute cycles and the ever-growing difficulty of system management. There is an increasing interest in the HPC community in using AI-based frameworks to tackle analytics and management problems in HPC so […]

Ayse Coskun Recognized in Computing Research

Prof. Coskun earns two awards and two major grants in computing research Energy-efficient computing expert Professor Ayse Coskun was most recently recognized with grants from the National Science Foundation (NSF) and Sandia National Laboratories, a best paper award, and an early career award. NSF awarded the interdisciplinary team led by Prof. Coskun $234K (total award $700K, shared between […]

Paschalidis Hosts Symposium on Control and Network Systems

in NEWS   by Liz Sheeley The 2nd Symposium on the COntrol of NEtwork Systems (SCONES) will be held on Monday, October 16 and Tuesday, October 17, 2017, at the Boston University Photonics Center. SCONES is being hosted by Professor Ioannis Paschalidis (ECE, BME, SE), the Editor-in-Chief of the IEEE Transactions on Control of Network Systems (TCNS), a publication sponsored by the IEEE Control Systems […]

CNS:CSR Collaborative Research: Leveraging Intra-chip/Inter-chip Silicon-Photonic Networks for Designing Next-Generation Accelerators

A little over a decade ago, GPUs were fixed-function processors built around a pipeline, dedicated to rendering 3-D graphics. In the past decade, as the potential for GPUs to provide massive compute parallelism became apparent, the software community developed new programming environments (CUDA and OpenCL) to leverage these massively parallel devices. Today, the leading graphics […]

XPS: FULL: CCA: Collaborative Research: Automatically Scalable Computation

For over thirty years, each generation of computers has been faster than the one that preceded it. This exponential scaling transformed the way we communicate, navigate, purchase, and conduct science. More recently, this dramatic growth in single processor performance has stopped and has been replaced by new generations of computers with more processors on them; […]