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.
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 […]
SHF: Small: Reclaiming Dark Silicon via 2.5D Integrated Systems with Silicon Photonic Networks
Emerging applications in the growing domains of cloud, internet-of-things, and high-performance computing require higher levels of parallelism and much larger data transfers compared to applications of the past. In tandem, power and thermal constraints limit the number of transistors that can be used simultaneously on a chip and this limit has led to the ?Dark […]
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; […]
Meeting Tomorrow’s Sustainability Demands Today
When it comes to high-powered computers, increased energy consumption and lack of reliability continue to be problems researchers are trying to overcome. Unfortunately, some of the best current methods for achieving these goals have their flaws. One example is seen in server consolidation, during which resources are shared across multiple applications and virtual CPUs. Without […]
CAREER: System-level Run-time Management Techniques for Energy-efficient Silicon-Photonic Manycore Systems
The general purpose computing capacity of the world has been increasing at an annual rate of more than 50% over the past few decades, and this trend is expected to continue in the future. However, this increasing compute capacity directly translates to increasing power dissipation. In fact, the server farms and data centers in US […]
CAREER: 3D Stacked Systems for Energy-Efficient Computing: Innovative Strategies in Modeling and Runtime Management
Energy efficiency is a central issue in computing. In large-scale computing clusters, operational and cooling costs impose significant sustainability challenges. Embedded systems run increasingly complex, performance demanding workloads, making the well-known energy management policies inadequate. High power densities also cause high on-chip temperatures and large thermal variations, both of which degrade system reliability. The research […]
CPS: Synergy: Data Driven Intelligent Controlled Sensing for Cyber Physical Systems
The goal of this project is to develop the foundations of a control and optimization science base for sensor networks viewed as complex systems operating in an uncertain and potentially adverse environment. The approach taken is a combination of addressing fundamental research issues while maintaining a focus on a specific target application domain, a manufacturing […]