Introduction
Edge AI continues to transform how data is processed in real time, especially in autonomous, industrial, and defense systems where latency, size, and reliability are critical.
AMD’s Versal® adaptive SoC family, introduced by Xilinx in 2019, brought a new class of heterogeneous computing by combining programmable logic, scalar processing, and the AI Engine (AIE).
In 2024, AMD announced the Versal Gen 2 portfolio, including the AI Edge and Prime Series—designed for intelligent edge and safety-critical applications. While some devices are still in early-adopter or evaluation phases, these platforms mark a major evolution toward higher efficiency and integration at the edge.
Versal Gen 1 AI Engine: The Foundation
Launched in 2019, the first-generation AI Engine (AIE v1) powered devices, such as the Versal AI Core VC1902, are targeting machine-learning inference and advanced signal processing.
Architecture Overview
- Tile-based compute array: A 2D grid of AI Engine tiles, each with a vector processor, a scalar RISC core, local SRAM, and AXI4-Stream/cascade interconnects.
- Vector unit: 512-bit SIMD datapath supporting INT4/8/16 and FP16/32 arithmetic.
- Local memory: Tens of KB per tile, accessible via deterministic inter-tile links.
- Integration: Tiles connect to the programmable logic (PL) and the Network-on-Chip (NoC) for high-speed data exchange.
A device like the VC1902 contains roughly 400 AI Engine tiles, achieving around 128–133 INT8 TOPS (theoretical) depending on clock and data type.
Developers use AMD Vitis™, programming in C/C++ kernels and graph-based dataflow models rather than HDL.
Versal Gen 2 AI Engine (AIE-ML v2): Optimized for the Edge
AMD’s Versal Gen 2 AI Edge and Prime Series, announced in 2024, build on AIE v1 with AIE-ML v2, offering higher efficiency, bandwidth, and edge-class reliability.
The architecture refines the tiled compute concept while adding advanced Arm® processing subsystems and embedded accelerators for video, imaging, and safety monitoring.
Architectural Enhancements
- Next-generation compute tiles:
AMD reports that AIE-ML v2 roughly doubles per-tile vector efficiency versus Gen 1 and supports additional data formats such as FP8 and mixed-precision MX6/MX9, improving energy efficiency for inference workloads. - Enhanced scalar complex:
Flagship Gen 2 devices integrate up to 8 Arm Cortex-A78AE application cores and 10 Cortex-R52 real-time cores, yielding up to ≈10× the scalar performance of Gen 1 subsystems, depending on workload. - Expanded on-chip memory:
Larger local and shared SRA, ranging from tens to hundreds of KB per tile and up to hundreds of Mbit aggregate, reduces data-movement latency and supports larger models. - Integrated accelerators:
On-chip Image Signal Processors (ISPs) and Video Codec Units (VCUs) (supporting up to 4K60 HEVC/AVC) offload pre/post-processing from the programmable logic. - Safety and efficiency:
Designed for ISO 26262 ASIL-D and SIL-3 targets, the architecture achieves up to ≈3× higher TOPS/W than Gen 1 under AMD-reported conditions.
(Performance improvements are AMD-reported and workload-dependent.)
Representative Comparison (Indicative)
| Feature | Versal Gen 1 (AIE v1) | Versal Gen 2 (AIE-ML v2) | Typical Improvement |
|---|---|---|---|
| Clock Frequency | Up to 1 GHz | ~1–1.25 GHz (target) | Similar / ↑ Speed grades |
| Vector Width | 512 bits | 512 bits | – |
| Data Types | INT4/8/16, FP16/32 | INT4/8, FP8, MX6/MX9 | Expanded formats |
| Scalar Subsystem | Dual RISC per tile | One RISC per tile | |
| Tile Memory | tens of KB per tile | larger (local + shared SRAM) | ↑ capacity |
| Efficiency | ~1 TOPS/W | up to ≈3 TOPS/W | ≈3× gain |
| Target Use | Datacenter, 5G, edge DSP | Automotive, industrial, defense AI | Edge-optimized |
(Values are representative; actual figures vary by SKU and workload.)
AI Engine vs. Traditional Vector or DSP Processing
While the AI Engine uses SIMD vector math, it differs significantly from CPU vector extensions (e.g., Arm SVE) or legacy DSP arrays:
- Distributed architecture: Each tile has its own compute + memory resources, minimizing shared-memory contention.
- Local SRAM: On-tile memory provides deterministic, low-latency data access, 10–100× faster than external DRAM.
- Predictable dataflow: Communication via AXI4-Stream creates low-jitter, real-time behavior ideal for control and inference.
- Vitis programmability: High-level C/C++ and dataflow graph design simplify complex AI pipelines.
For mixed workloads, DSP slices in the programmable logic remain ideal for high-precision signal paths (e.g., FIR, FFT), while the AI Engines deliver dense compute for parallel, low-precision inference—offering a complementary balance.
The SundanceDSP SE2000: Bringing Versal Gen 2 to the Rugged Edge
The SundanceDSP SE2000 3U OpenVPX module extends this architecture to deployed, rugged environments.
It is designed to leverage the AMD Versal Gen 2 AI Edge device, anticipated to include the AIE-ML v2 array, Arm A78AE/R52 processing, and high-speed VPX/SOSA I/O for mission-critical edge AI.
The SE2000’s combination of heterogeneous compute, ruggedized VPX design, and SOSA alignment positions it for:
- Real-time sensor fusion
- Autonomous vehicle control
- Edge inference in defense and aerospace systems
Conclusion
AMD’s Versal Gen 2 AI Engine advances the original AIE concept with higher compute efficiency, expanded precision formats, larger memory, and robust safety integration—tailored for embedded AI and deterministic control.
Through platforms such as the SundanceDSP SE2000, this technology transitions from data-center R&D to field-deployable edge intelligence, enabling next-generation mission-critical AI systems.