The rapid evolution of Machine Learning (ML) workloads, particularly Deep Neural Networks (DNNs) and Transformer-based models, has intensified demands on computing architectures, highlighting the limitations of traditional von Neumann systems due to the me ...
Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and ...
To achieve resource-efficient hardware designs, high-level synthesis (HLS) tools share (i.e., time-multiplex) functional units among operations of the same type. This optimization is typically performed in conjunction with operation scheduling to ensure th ...
Vision systems built around conventional image sensors have to read, encode and transmit large quantities of pixel information, a majority of which is redundant. As a result, new computational imaging sensor architectures were developed to preprocess the r ...
Dataflow circuits promise to overcome the scheduling limitations of standard HLS solutions. However, their performance suffers due to timing overheads caused by their handshake communication protocol. Current pipelining solutions fail to account for logic ...
In order to optimize the energy use of servers in Data Centers, techniques such as power capping or power budgeting are usually deployed. These techniques rely on the prediction of the power and execution time of applications. These data are obtained via d ...
