The Intel® Movidius™ Myriad™ X VPU is the third generation and most advanced VPU from Intel. It is the first of its class to feature the Neural Compute Engine – a dedicated hardware accelerator for deep neural network inferences. The Neural Compute Engine in conjunction with the 16 powerful SHAVE cores and an ultra-high throughput intelligent memory fabric makes Intel Movidius Myriad X the industry leader for on-device deep neural networks and computer vision applications. Intel’s Myriad™ X VPU has received additional upgrades to imaging and vision engines including additional programmable SHAVE cores, upgraded and expanded vision accelerators, and a new native 4K ISP pipeline with support for up to 8 HD sensors connecting directly to the VPU.
The Intel Movidius Myriad X VPU is programmable via the Myriad Development Kit (MDK) which includes all necessary development tools, frameworks and APIs to implement custom vision, imaging and deep neural network workloads on the chip.
Key Benefits
-Dedicated Neural Compute Engine
-16 High Performance SHAVE Cores
-Enhanced ISP with 4K support
-New Vision Accelerators including Stereo Depth
NVIDIA HGX Platform is designed for high-performance computing, supporting advanced AI model training and large-scale data analytics. It is essential for industries requiring extensive computational power for tasks like scientific research and complex simulations.
NVIDIA HGX Platform offers exceptional performance and scalability, delivering robust AI and high-performance computing capabilities. Its advanced architecture facilitates efficient processing and seamless integration with existing workflows. Known for its reliability and flexibility, it excels in handling complex computational tasks, offering enhanced speed and optimized resource utilization. It effectively manages large datasets for quicker data analysis and model training, making it a valuable asset in data-intensive environments.
What are the key features of NVIDIA HGX Platform?Industries implementing NVIDIA HGX Platform benefit from its advanced computational capabilities, making it indispensable for scientific research, complex simulations, and AI data processing. Its scalability and efficiency in managing GPU resources optimize machine learning workflows, significantly enhancing computational precision.
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