Various natural language processing (NLP) tasks necessitate deep models that are fast, efficient, and small based on their ultimate application at the edge or elsewhere. While significant investigation has furthered the efficiency and reduced the size of these models, reducing their downstream latency without significant trade-offs remains a difficult task....
This thesis presents a novel design for a rheometer style viscometer by implementing high temperature and inert atmospheric requirements on the device. The goals of this device are to measure the viscosity of high temperature molten salts, which are corrosive and extremely hydroscopic. It also aims to be able to...
Machine learning has enabled significant advancements in diverse fields, yet, with a few exceptions, has had limited impact on computer architecture. Recent work, however, has begun to explore broader application to design, optimization, and simulation. Notably, machine-learning-based strategies often surpass prior state-of-the-art analytical, heuristic, and human-expert approaches. This thesis first...
As the number of nodes in high-performance computing (HPC) systems continues to grow, it becomes increasingly important to design scalable interconnection network topologies. Prior work has shown promise in adding random shortcuts on top of an existing topology to reduce average hop count and network diameter, but has been limited...
Advances in deep learning based image processing have led to their adoption for a wide range of applications, and in tow with these developments is a dramatic increase in the availability of high quality datasets. With this comes the need to accelerate and scale deep learning applications in order to...
Data centers have seen a rapid growth in recent years as the technology industry is relying more on cloud services. In effect, data centers are paying millions of US $ in energy costs. Several strategies have been proposed to lower the total energy cost at data centers- task migration, server...
Routerless networks on chip (NoCs) were recently introduced as an alternative to traditional mesh-based scalable networks, promising improved performance and scalability with a large decrease in power and area usage by the elimination of routing on in-flight packets. Without mitigation, most network designs, including routerless, are susceptible to loss of...
The machine learning and deep learning models have been very lightly explored in analyzing the behavior of On-Chip network traffic. These models have proven their potential in pattern recognition, classification etc... In this paper we analyze the spatial pattern that each workload exhibits in its life cycle during execution. We...
Resource Planning and Management (RPM) network is a graphical
representation of input-output relationships among activities and
resources within a system. Both resources (events) and activities
(decisions) are explicitly represented as nodes in all RPM networks.
Depending upon the relationships being depicted, RPM networks can
be classified into Relational (R), Precedence...