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GTC ON-DEMAND

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Abstract:

Detecting road users in real-time is key to enabling safe autonomous driving applications in crowded urban environments. The talk presents a distributed sensor infrastructure being deployed in the city of Modena (Italy) at the heart of the Italian 'Motor Valley'. Modena's Automotive Smart Area (MASA) connects hundreds of smart cameras, supporting embedded GPU modules for edge-side real-time detection, with higher performance GPU (fog) nodes at block level and low latency wireless V2X communication. A distributed deep learning paradigm balances precision and response time to give autonomous vehicles the required sensing support in a densely populated urban environment. The infrastructure will exploit a novel software architecture to help programmers and big data practitioners combine data-in-motion and data-at-rest analysis while providing Real-Time guarantees. MASA; funded under the European project CLASS, is an open testbench where interested partners may deploy and test next-generation AD applications in a tightly connected setting.

Detecting road users in real-time is key to enabling safe autonomous driving applications in crowded urban environments. The talk presents a distributed sensor infrastructure being deployed in the city of Modena (Italy) at the heart of the Italian 'Motor Valley'. Modena's Automotive Smart Area (MASA) connects hundreds of smart cameras, supporting embedded GPU modules for edge-side real-time detection, with higher performance GPU (fog) nodes at block level and low latency wireless V2X communication. A distributed deep learning paradigm balances precision and response time to give autonomous vehicles the required sensing support in a densely populated urban environment. The infrastructure will exploit a novel software architecture to help programmers and big data practitioners combine data-in-motion and data-at-rest analysis while providing Real-Time guarantees. MASA; funded under the European project CLASS, is an open testbench where interested partners may deploy and test next-generation AD applications in a tightly connected setting.

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Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8254
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Abstract:

High-performance embedded platforms, like Nvidia Parker and upcoming Xavier architecture, have the potential of revolutionizing traditional safety-critical domains, where innovative automotive and avionic applications are being proposed to safely replace human activities. However, these domains require sound guarantees be given not only on the functional correctness but also on the timing delays of the critical activities, according to well defined safety standards (e.g., ISO26262). In this talk, we will explain how predictability can be achieved on inherently unpredictable multi-core systems, analyzing the main timing bottlenecks of these challenging platforms, and presenting a holistic framework that aims at overcoming them to achieve predictable performance.

High-performance embedded platforms, like Nvidia Parker and upcoming Xavier architecture, have the potential of revolutionizing traditional safety-critical domains, where innovative automotive and avionic applications are being proposed to safely replace human activities. However, these domains require sound guarantees be given not only on the functional correctness but also on the timing delays of the critical activities, according to well defined safety standards (e.g., ISO26262). In this talk, we will explain how predictability can be achieved on inherently unpredictable multi-core systems, analyzing the main timing bottlenecks of these challenging platforms, and presenting a holistic framework that aims at overcoming them to achieve predictable performance.

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Topics:
Intelligent Machines, IoT & Robotics, Autonomous Vehicles, Real-Time Graphics
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23182
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