NECSTTechTalk
ReWArDS - Reconfigurable hardWare for Artificial intelligence and Data Science
Luca Stornaiuolo
PhD student at NECSTLab
DEIB - NECSTLab
this event will be online from Facebook
June 11th, 2020
11.00 am
Contacts:
Marco Santambrogio
Luca Stornaiuolo
PhD student at NECSTLab
DEIB - NECSTLab
this event will be online from Facebook
June 11th, 2020
11.00 am
Contacts:
Marco Santambrogio
Sommario
On June 11th, 2020 at 11.00 am a new “NECSTSTechTalk” will take place from Facebook on "ReWArDS - Reconfigurable hardWare for Artificial intelligence and Data Science".
Hardware accelerators are an effective solution to increase the performance of algorithms in a wide array of disciplines, from Data Science to Scientific Calculus. However, data scientists and mathematicians often do not have the required knowledge or time to fully exploit these accelerators, and they perceive them as difficult and frustrating to use.
Furthermore, Artificial Neural Networks are becoming the base of many of these applications, both in embedded and in server-class contexts. While Graphics Processing Units (GPUs) are predominantly used for training, solutions for inference often rely on Field Programmable Gate Arrays (FPGAs) since they are more flexible and cost-efficient in many scenarios.
The main goal is employing FPGA systems for processing huge quantities of data, that may be analyzed in real time, in order to provide a ready-to-use valuable solution to data scientists and mathematicians and applying FPGA systems to machine learning and AI applications to have a power efficient solution for complicated analytics problems.
The NECSTLab is a DEIB laboratory, with different research lines on advanced topics in computing systems: from architectural characteristics, to hardware-software codesign methodologies, to security and dependability issues of complex system architectures.
Streaming event from Facebook page:https://www.facebook.com/NECSTLab
Hardware accelerators are an effective solution to increase the performance of algorithms in a wide array of disciplines, from Data Science to Scientific Calculus. However, data scientists and mathematicians often do not have the required knowledge or time to fully exploit these accelerators, and they perceive them as difficult and frustrating to use.
Furthermore, Artificial Neural Networks are becoming the base of many of these applications, both in embedded and in server-class contexts. While Graphics Processing Units (GPUs) are predominantly used for training, solutions for inference often rely on Field Programmable Gate Arrays (FPGAs) since they are more flexible and cost-efficient in many scenarios.
The main goal is employing FPGA systems for processing huge quantities of data, that may be analyzed in real time, in order to provide a ready-to-use valuable solution to data scientists and mathematicians and applying FPGA systems to machine learning and AI applications to have a power efficient solution for complicated analytics problems.
The NECSTLab is a DEIB laboratory, with different research lines on advanced topics in computing systems: from architectural characteristics, to hardware-software codesign methodologies, to security and dependability issues of complex system architectures.
Streaming event from Facebook page:https://www.facebook.com/NECSTLab