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With NXP LayerScape 16-core processor
Twice the processing performance compared to the previous generation Blue Box
Provides ASIL D compliance processing and verification capabilities
To develop differentiated vehicles, manufacturers are seeking to create "user-defined vehicles," allowing consumers to add smart, connected device features to their vehicles. This requires solutions that securely connect these devices to the vehicle.
NXP Semiconductors announced on the 12th 'BlueBox 3.0', a new expanded version of its Automotive High-Performance Compute (AHPC) development platform.

BlueBox 3.0 is a platform for developing and verifying software applications prior to commercialization of semiconductor products. This release provides a flexible way to implement evolving automotive architectures, including custom vehicles, Level 2+ (L2+) autonomous driving, and connected cars.
Designers can accelerate system development cycles and time to market by supporting Kalray's Massively Parallel Processor Array (MPPA) processor-based PCIe cards and centralized compute modules that enable heterogeneous acceleration, secure, high-performance NXP processors, and expanded I/O connectivity and extensions.
BlueBox 3.0 leverages the NXP Layerscape LX2160A 16-core processor, doubling processing performance compared to the previous generation BlueBox. This enables it to accommodate vision, radar, and LiDAR signal paths for advanced sensor fusion applications.
It also offers scalable options for AI and ML acceleration through Kalray's Coolidge™ MPPA processor, which can be applied to new connected services such as perception, prediction, and pathfinding capabilities. Furthermore, the integration of the NXP S32G processor provides reliable safety processing and verification capabilities for secure vehicle networking and system-level ASIL D compliance.
NXP and Kalray are offering the BlueBox 3.0 Software Development Environment (SDE), which integrates the Kalray MPPA processor. It also supports NXP's eIQ Auto Machine Learning toolkit to meet evolving performance requirements.
Twice the processing performance compared to the previous generation Blue Box
Provides ASIL D compliance processing and verification capabilities
To develop differentiated vehicles, manufacturers are seeking to create "user-defined vehicles," allowing consumers to add smart, connected device features to their vehicles. This requires solutions that securely connect these devices to the vehicle.
NXP Semiconductors announced on the 12th 'BlueBox 3.0', a new expanded version of its Automotive High-Performance Compute (AHPC) development platform.
▲ NXP BlueBox 3.0 [Photo = NXP]
BlueBox 3.0 is a platform for developing and verifying software applications prior to commercialization of semiconductor products. This release provides a flexible way to implement evolving automotive architectures, including custom vehicles, Level 2+ (L2+) autonomous driving, and connected cars.
Designers can accelerate system development cycles and time to market by supporting Kalray's Massively Parallel Processor Array (MPPA) processor-based PCIe cards and centralized compute modules that enable heterogeneous acceleration, secure, high-performance NXP processors, and expanded I/O connectivity and extensions.
BlueBox 3.0 leverages the NXP Layerscape LX2160A 16-core processor, doubling processing performance compared to the previous generation BlueBox. This enables it to accommodate vision, radar, and LiDAR signal paths for advanced sensor fusion applications.
It also offers scalable options for AI and ML acceleration through Kalray's Coolidge™ MPPA processor, which can be applied to new connected services such as perception, prediction, and pathfinding capabilities. Furthermore, the integration of the NXP S32G processor provides reliable safety processing and verification capabilities for secure vehicle networking and system-level ASIL D compliance.
NXP and Kalray are offering the BlueBox 3.0 Software Development Environment (SDE), which integrates the Kalray MPPA processor. It also supports NXP's eIQ Auto Machine Learning toolkit to meet evolving performance requirements.
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