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Five AMD Versal Features for Vision Processing

Considering a move from AMD Zynq UltraScale+ to AMD Versal for image processing?

Explore the hardened ISP, AI Engines, NoC and memory, processor partitioning and video encoding. Understand how to use each feature—and what to measure against your current system.

Download the guideInside the guide

From component selection to integration

FPGA & SoM modules

Flexible AMD Zynq™ UltraScale+™, AMD Versal™, RFSoC, Agilex V and PolarFire modules.

Digitizers and AWGs

FPGA- and GPU-based digitizer and AWG solutions, from 5 MSPS to 10 GSPS.

Software-defined radio

SDR chips and modules covering 0 to 10 GHz.

Custom engineering

Custom board design and FPGA and GPU firmware development.

Resources

Inside the guide

Five architecture decisions, explained through practical image-processing pipelines. The guide focuses on selected AMD Versal AI Edge Series Gen 2 devices; feature availability depends on the device.

1. Hardened image signal processing

Follow RAW camera data through the ISP, then decide which sensor corrections and custom processing remain in programmable logic. Learn where a hardened pipeline can release FPGA resources compared with a PL-based AMD Zynq UltraScale+ implementation—and why thermal calibration needs separate consideration.

2. AIE-MLv2 AI Engines

Explore inference acceleration, supported precision, tiling and local-memory reuse. The guide explains how to partition preprocessing, inference and postprocessing, and why sustained frame rate depends on data movement as much as peak compute.

3. NoC and next-generation memory

Trace camera capture, frame buffers, inference and encoding through shared memory. Examine bandwidth budgets, burst traffic and quality-of-service settings to compare a Versal architecture with your measured ZU+ system.

4. Cortex-A78AE and Cortex-R52 processors

Separate application software from deterministic control tasks. The guide covers processor partitioning, DMA ownership, cache coherency and the handoff between Linux, real-time software and hardware accelerators.

5. Enhanced video codec integration

Evaluate encoding alongside vision analytics: memory traffic, codec configuration, latency and stream requirements. Compare the selected Versal device with your current system, including ZU+ EV devices that already include a video codec unit.

Each section connects the feature to an application, explains how to use it and identifies what to measure before committing to migration.

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Inside the guide

Five architectural features to evaluate when moving from AMD Zynq UltraScale+ to selected AMD Versal AI Edge Series Gen 2 devices. Understand where hard IP, AI Engines, programmable logic and Arm processors fit—and what must be measured before choosing a device.

1. Hardened image signal processing

Understand how dedicated ISP tiles can move supported RAW sensor conditioning out of programmable logic. Check input patterns, pixel packing, bit depth, throughput and output formats before assigning demosaicing, correction and colour processing to the hardened path. Keep custom interfaces, timestamping and unsupported corrections in PL.

The guide explains how to budget parallel output streams and compare LUT, DSP and BRAM use, power and end-to-end latency with your existing ZU+ pipeline. This feature matters when your application includes compatible sensor data; it is not a requirement for every embedded system.

2. AIE-MLv2 AI Engines

Explore the separate vector-compute array, tile-local memories and streaming interconnects. Partition acquisition and deterministic transforms in PL, supported inference or vector kernels in AI Engines, and application control on Arm processors. Operator support, tensor tiling and supported numerical formats determine what can actually be mapped.

Learn why local-memory reuse and DDR spills can dominate sustained throughput. Compare accuracy, latency, batch size, concurrent workloads and board power with the same ZU+ baseline. Peak TOPS alone cannot establish an application-level improvement.

3. Network on Chip and next-generation memory

Build a traffic budget for every producer, consumer and buffer: payload rate, read/write passes, burst behaviour, memory destination and latency class. The dedicated NoC connects processors, accelerators, PL and memory controllers; route selection and quality-of-service settings affect service under contention.

The guide uses a concrete bandwidth calculation to show how a modest input rate becomes a much larger DDR load after repeated passes. Learn when streaming and on-chip retention help, and how to measure usable bandwidth, tail latency and dropped data with all concurrent masters active.

4. Cortex-A78AE and Cortex-R52 processors

Separate Linux application services from bounded real-time control. Define the APU/RPU split, interrupt handling, shared-buffer ownership and interprocessor communication. Check coherent versus noncoherent DMA paths explicitly; an accelerator accessing shared memory does not automatically guarantee cache coherency.

Understand how local memories and R52 operating modes influence scheduling and independent-core availability. Compare CPU headroom and worst-case deadline response with equivalent software, peripheral traffic and thermal conditions on ZU+.

5. Enhanced video codec integration

Evaluate hardened AVC/H.264 and HEVC/H.265 encoding and decoding as part of the complete data path. Verify device-specific pixel formats, bit depth, aggregate throughput, rate control and latency alongside colour conversion, buffers and packetisation.

The guide explicitly accounts for ZU+ EV devices that already contain a hardened VCU. Attribute any benefit to supported formats, simultaneous workloads, power or system consolidation, rather than assuming a generic compression gain. Keep time-critical metadata independent of the encoded stream.

Each section includes how to use the feature, what benefit to target, implementation steps, design-review questions and measurements against an AMD Zynq UltraScale+ baseline. Availability varies by device; the five features are not shared by every AMD Versal family.