Deep Learning Processor

The videantis processors are the most efficient deep learning, computer vision, signal processing, and video coding processing solutions on the market. Its subsystems run all embedded computing tasks on a single software-programmable and scalable processor architecture.

Processors that do more

videantis’ efficient processing subsystems run deep learning, computer vision, signal processing, imaging, and video coding on the same compute platform. This reduces power consumption, bandwidth, and simplifies software development and integration.

To efficiently run deep convolutional nets in real-time requires extreme performance levels and careful optimization, which videantis addresses with its v-MP6000UDX processor IP and optimization tools.

Unified architecture

The unified architecture runs all embedded processing tasks.
This saves power and silicon area, reduces time-to-market, and extends product life.

Deep learning

Deep learning and AI are transforming industries.
Whether it’s at the edge or in the cloud, videantis has the solution to bring deep learning into the consumer’s hands.

• Easy hardware integration: videantis provides full subsystems that include a memory hierarchy, multiple processors, a bus fabric or network-on-chip, and various system interfaces. The processing subsystems are ready for integration into SoC designs with minimal design work and proven power, performance, and area results.
• Single integrated software tool flow: Whether it’s deep learning, computer vision, signal processing, imaging, codecs, or generic algorithm acceleration using OpenCL, all software components are developed using a single programming toolset. This reduces the development effort and bugs, and maximizes performance.
• Minimize data bandwidth: Instead of moving data around between accelerators and different processor subsystems, everything is kept local in the v-MP6000UDX subsystem. This lowers bandwidth and ensures that compute engines will not be starved for data any more.