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What is eMCOS?

An advanced application framework built for autonomous driving technologies harnesses a wide array of collective data to interpret the surrounding environment and autonomously make informed driving choices. This framework is underpinned by a scalable distributed computing architecture that utilizes many-core processors in conjunction with different types of processors to provide the necessary computational strength for complex data processing. Additionally, the platform is crafted to be flexible, allowing software applications to function seamlessly across various hardware resources while upholding real-time performance to ensure safety and dependability in autonomous tasks. Such adaptability guarantees that the system can progress in tandem with technological innovations and evolving operational demands, fostering a future-ready approach to autonomous driving solutions. This ensures that the platform can continuously integrate new features and improvements as the landscape of autonomous driving evolves.

What is NVIDIA DRIVE?

The integration of software transforms a vehicle into an intelligent machine, with the NVIDIA DRIVE™ Software stack acting as an open platform that empowers developers to design and deploy a diverse array of advanced applications for autonomous vehicles, including functions such as perception, localization and mapping, planning and control, driver monitoring, and natural language processing. Central to this software ecosystem is DRIVE OS, hailed as the inaugural operating system specifically engineered for secure accelerated computing. This robust system leverages NvMedia for sensor input processing, NVIDIA CUDA® libraries to enable effective parallel computing, and NVIDIA TensorRT™ for real-time AI inference, along with a variety of tools and modules that unlock hardware capabilities. Building on the foundation of DRIVE OS, the NVIDIA DriveWorks® SDK provides crucial middleware functionalities essential for the advancement of autonomous vehicles. Key features of this SDK include a sensor abstraction layer (SAL), multiple sensor plugins, a data recording system, vehicle I/O support, and a framework for deep neural networks (DNN), all of which are integral to improving the performance and dependability of autonomous systems. By harnessing these powerful resources, developers find themselves better prepared to explore innovative solutions and expand the horizons of automated transportation, fostering a future where smart vehicles can navigate complex environments with greater autonomy and safety.

Media

Media

Integrations Supported

Cerbrec Graphbook
Coiled
Dell AI-Ready Data Platform
Dive
E2E Cloud
Echo AI
Google Cloud Confidential VMs
Google Cloud Deep Learning VM Image
Magic Bullet
Maxint
NVIDIA Onyx
RightNow AI
SERA
Solvision Invoicing
Swarm
Urban SDK
Zappit AI
harrison.ai
phoenixNAP

Integrations Supported

Cerbrec Graphbook
Coiled
Dell AI-Ready Data Platform
Dive
E2E Cloud
Echo AI
Google Cloud Confidential VMs
Google Cloud Deep Learning VM Image
Magic Bullet
Maxint
NVIDIA Onyx
RightNow AI
SERA
Solvision Invoicing
Swarm
Urban SDK
Zappit AI
harrison.ai
phoenixNAP

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

eSOL

Company Website

www.esol.com/embedded/emcos_autoware.html

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

www.nvidia.com/en-us/self-driving-cars/drive-platform/software/

Categories and Features

IoT

Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization

Categories and Features

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