The rapid growth of demanding applications in domains applying multimedia processing
and machine learning has marked a new era for edge and cloud computing. These …

Deep neural networks (DNNs) with embedding layers are widely adopted to capture
complex relationships among entities within a dataset. Embedding layers aggregate multiple …

Improving the performance of applications is a core target of computer systems research and
has led to the creation of various techniques. Among them is function memoization, an …

In high performance processors, the design of on-chip memory hierarchies is crucial for
performance and energy efficiency. Current processors rely on large shared Non-Uniform …

The challenging deployment of compute-intensive applications from domains such Artificial
Intelligence (AI) and Digital Signal Processing (DSP), forces the community of computing …

Historically, continuous improvements in general-purpose processors have fueled the
economic success and growth of the IT industry. However, the diminishing benefits from …

With increasing core counts, the scalability of directory-based cache coherence has become
a challenging problem. To reduce the area and power needs of the directory, recent …

Function memoization is an optimization technique that reduces a function call overhead
when the same input appears again. A table that stores the previous result is searched and …

Computational efficiency is a critical constraint for a variety of cutting-edge real-time
applications. In this work, we identify an opportunity to speed up the end-to-end runtime of …

Performance is a key quality of modern software. Although recent years have seen a spike in
research on automated improvement of software's execution time, energy, memory …