Intel Tiger Lake

Intel® Tiger Lake

The 11th generation Intel® Core™ processors are based on third-generation 10nm process technology and offer a balance between performance and responsiveness on a low-power platform. The powerful CPU of the Tiger Lake platform comes with up to 23% faster single-thread and up to 19% faster multi-thread performance. Graphics performance is up to 2.95 times faster thanks to the new Intel® Iris® Xe graphics and supports PCI Express 4.0 and Thunderbolt™ 4/USB4.
Specifically designed for time-sensitive, low-latency applications, this platform brings enough power to run multiple workloads simultaneously, including AI and deep learning applications.

Other special features include:

Real-time

For many applications, the combination of a powerful CPU and GPU is mandatory. AI and deep-learning capabilities enable the consolidation of workloads. Application examples include computer numerical control (CNC) machines, real-time control systems, human-machine interfaces, tool applications, medical imaging and diagnostics (in applications such as ultrasound), and other applications that require high-resolution HDR output with AI capabilities.

Fast cycle times

For many new IoT applications, timely performance is a must. Intel® Time Coordinated Computing (Intel® TCC) helps implement fast cycle times and low latency for applications such as programmable logic controllers (PLCs) and robotics.

Multimedia

The integrated graphics engine can display up to 4x4k60 HDR or 2x8K60 SDR. It can also decode over 40 incoming video streams at 1080p and 30 frames per second. These features are ideal for applications such as digital signage and network video recorders, as well as computer vision with inference capabilities for application areas such as machine vision and machine inspection.

Deep Learning

AI (Artificial Intelligence) and inferencing applications can be implemented using Intel® DL (Deep Learning) Boost, which runs on the Vector Neural Network instructions (VNNI) of the CPU or with 8-bit integer instructions on the GPU (Int8). 

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