Data Orchestration 2 609edab7808b5

Data Orchestration Supports the Next Advance in AI

May 18, 2021
AI and ML technologies now power a rapidly expanding range of products and applications from embedded systems to hyperscale data centers. Learn how FPGA based data orchestration engines enable efficient data movement across the AI network.

Deep-learning technology demands numerous tensor arithmetic operations. To support real-time execution, memory and processor performance must meet higher targets than possible with standard software-driven architectures. This leads to the use of designs based on FPGA hardware accelerators performing parallelized and heavily pipelined tensor-arithmetic operations. To avoid pipeline stalls, data must be in the right place, at the right time and in the right format. Learn how FPGA based orchestration hardware overcomes accelerator pipelines stalling and allows operation at peak efficiency.

Sponsored

Explore common applications, the difference between a coupled inductor and a transformer, how to choose a coupled inductor, and more.
Slide switches offer a compact, reliable way to control circuits with a simple sliding motion—ideal for low-power, space-constrained applications. This technical overview breaks...
Learn how Single Pair Ethernet (SPE) contributes to sustainability in industrial communication. This on-demand webinar explores how SPE reduces wiring, installation costs, and...
Wireless is no longer an add-on-it's central to the performance, scalability, and future-readiness of modern embedded systems.