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Intel introducing new processor series dedicated for automotive applications

Intel is developing a new processor series dedicated for automotive applications. The A3900 series will enable a complete software-defined cockpit solution that incudes in-vehicle infotainment (IVI), digital instrument clusters and advanced driver assistance systems (ADAS)—all in a single, compact and cost-effective SoC.

Intel announced the new automotive processor family along with its introduction of the new Intel Atom processor E3900 series for the Internet of Things (IoT). The A3900 series will allow car makers to offer new levels of determinism for real-time decision-making required in next-generation cars. It is currently sampling with customers and will be available in Q1 2017.

The new Intel Atom automotive processors deliver excellent memory speeds and bandwidth (up to LPDDR4 2400 and 38.4 GB/s) in a compact, low-power package. They offer fast graphics and HD video for media-centric applications, with support for 4K video at 60 Hz.

This latest Intel Atom SoC achieves new levels of image and video processing power in a compact form factor. Intel Time Coordinated Computing Technology (Intel TCC Technology) makes more demanding and real-time video analytics possible in smart and connected vehicles. TCC coordinates and synchronizes peripherals and networks of connected devices, achieving improved determinism and resolving latency issues.

The SoC integrates numerous specialized processors, including an energy-efficient quad-core CPU, a powerful GPU, and dedicated audio, video, and image processors. It also delivers the ability to handle more sensors and tasks.

Built into a compact flip chip ball grid array (FCBGA) (a type of surface-mount packaging) and featuring Intel 14 nm silicon technology, the Intel Atom SoC offers a new graphics engine that doubles the image processing vectors, greatly expanding its video capabilities.

Virtualization Technology for Directed I/O (VT for Directed I/O) provides hardware support for isolating and restricting device access and I/O device assignment. This ensures key safety functions get priority in terms of access to the processor, driving the consolidation of IVI and instrument clusters.

These new processors are available as an automotive compute module featuring integrated power management and memory. Automotive-qualified modules meet the Automotive Electronics Council AEC-Q100 standard for stress test qualification for integrated circuits, with SKUs that offer a -40°C to 110°C temperature rating and a seven-year lifetime for industrial applications. The module is pre-validated with Intel’s automotive software tools and multiple OSs, so suppliers can build simpler printed circuit board (PCB) solutions.

With advanced protection at the hardware level, these processors can help reduce vulnerabilities. They feature an integrated converged security engine, a dedicated security coprocessor that dynamically adapts the security level to function criticality. They also offer secure boot and fast cryptographic execution with Intel AES New Instructions (Intel AES-NI).

To speed and simplify development, Intel and its partners provide a comprehensive set of developer tools and third-party OS support, including:

  • The Intel C++ Compiler, VTune Amplifier for Systems, and Graphics Performance Analyzer

  • Reference stacks, including an IVI middleware and automotive boot loader

  • Reference OS support for Linux, Android Auto, Green Hill, QNX, and Wind River Helix Cockpit

  • Hypervisors for multi-OS systems from QNX, Green Hill, and Mentor Graphics

  • Performance-tuning tools for the Intel-based CPU and GPU and complete hardware development vehicles

E3900 series for IoT. The Intel Atom processor E3900 series will make the edge and fog more intelligent—enabling many of the processing needs to take place at or near the data sensor and alleviating the need to push all processing to the data center. Fog computing, also known as fog networking, is a decentralized computing infrastructure in which computing resources and application services are distributed in the most logical place at any point from the data source to the cloud.

As an example, consider traffic cams and sensor data. There are significant downsides to sending data to a server for analysis, such as loss due to video compression and time spent in travel, versus having the ability to process data at the device.

In the automotive industry, the software-defined cockpit is also where this edge computing capability can make a difference. The ability for a single system to drive the digital gauges, navigation, and advance driver assist functions is the trend. It is important that backup sensors, bird’s-eye view parking or side collision alter function in a reliable response time, regardless of what the media or navigation system is doing at that time.



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