Machine learning (ML) has become a prevalent approach to tame the complexity of design
space exploration for domain-specific architectures. While appealing, using ML for design …

High-level synthesis (HLS) tools automatically transform a high-level program, for example
in C/C++, into a low-level hardware description. A key challenge in HLS tools is scheduling …

Runtime systems are commonly used by parallel applications in order to efficiently exploit
the underlying hardware resources. A runtime system hides the complexity of the …

Modern deep learning (DL) applications are built using DL libraries and frameworks such as
TensorFlow and PyTorch. These frameworks have complex parameters and tuning them to …

Nowadays, engineers have to develop software often without even knowing which hardware
it will eventually run on in numerous mobile phones, tablets, desktops, laptops, data centers …

The emergence of CNNs in mainstream deployment has necessitated methods to design
and train efficient architectures tailored to maximize the accuracy under diverse hardware & …

This article aims to tackle two fundamental memory bottlenecks: limited off-chip bandwidth
(bandwidth wall) and long access latency (memory wall). To achieve this goal, our approach …

Understanding dynamic program behavior is critical in many stages of the software
development lifecycle, for purposes as diverse as optimization, debugging, testing, and …

In recent years, the focus of computing has moved away from performance-centric serial
computation to energy-efficient parallel computation. This necessitates run-time optimisation …

In critical embedded systems especially hard real time systems, worst-case execution time
analysis is considered rather than expensive testing tools. In real time, most of the …