Simultaneous Localization And Mapping (SLAM) is a key component of self-driving cars. We study ORB-SLAM, a SLAM state-of-the-art solution, and develop a hardware accelerator for a critical part of it: ORB feature extraction. ...

These days, working with deep neural networks goes hand in hand with the use of GPUs. Once a deep neural network has been trained for hours, days, or even weeks on a desktop GPU, it is deployed in the field where it runs ...

Parallel programming presents an efficient solution to exploit future multicore processors. Unfortunately, traditional programming models depend on programmer’s skills for synchronizing concurrent threads, which makes ...

This master thesis characterizes the performance and energy bottlenecks of speech recognition systems when running on modern GPU, with the aim of providing useful information for designing future GPU architectures, as well ...

This thesis takes a HW/SW collaborative approach to tackle the problem of computational inefficiency in a holistic manner. The hardware is redesigned by restraining the datapath to merely 16-bit datawidth (integer datapath ...

Power constraints led to the end of exponential growth in single–processor performance, which characterized the semiconductor industry for many years. Single–chip multiprocessors allowed the performance growth to continue ...

The computation capabilities of mobile GPUs have greatly evolved in the last generations, allowing real-time rendering of realistic scenes. However, the desire for processing complex environments clashes with the ...

Graph processing is an established and prominent domain that is the foundation of new emerging applications in areas such as Data Analytics and Machine Learning, empowering applications such as road navigation, social ...

GPU architectures have become popular for executing general-purpose programs. Moreover, they are some of the most efficient architectures for machine learning applications which are among the most trendy and demanding ...