XCVM1802-2LSEVSVD1760
Versal AI Core ACAP with 400 AI Engines, 1,968 DSP engines, 1.85M logic cells for AI inference.
Product Overview
Description
The XCVM1802-2LSEVSVD1760 is a high-performance Versal AI Core ACAP featuring 400 AI Engines delivering up to 133 INT8 TOPS for AI inference acceleration. The device includes 1,968 DSP engines for additional signal processing and 1,852,000 system logic cells in the adaptable engine.
The scalar engine features dual-core ARM Cortex-A72 application processors and dual-core Cortex-R5 real-time processors for heterogeneous computing. The device includes 152 GTY transceivers supporting up to 58 Gbps PAM4 for high-speed connectivity.
With the revolutionary Network on Chip providing up to 1 TB/s bandwidth and support for DDR4 memory up to 3,200 Mbps, this ACAP targets AI inference, 5G baseband processing, radar, and data center acceleration applications.
Product Series
XCVM
Primary Application
AI Inference
Key Features
- High efficiency and reliability
- Optimized for industrial applications
- Comprehensive technical support
- Available from stock
Specifications
| AI Engines | 400 (133 INT8 TOPS) |
|---|---|
| DSP Engines | 1,968 |
| Logic Cells | 1,852,000 |
| Application Processor | Dual-core Cortex-A72 |
| Real-time Processor | Dual-core Cortex-R5 |
| GTY Transceivers | 152 (58 Gbps PAM4) |
| Memory | DDR4 up to 3,200 Mbps |
| Package | SVD1760 (45x45mm) |
Applications
AI Inference
Electronic system design
5G Baseband
Electronic system design
Radar Processing
Electronic system design
Data Center
Electronic system design
FAE Expert Insights
"The Versal AI Core VM1802 is paradigm shift in adaptive computing. The 400 AI Engines are the game-changer - I've seen 50-100x performance improvements in AI inference compared to traditional FPGA implementations. The AI Engines are programmed in C/C++ using the Vitis toolchain, making them accessible to software developers. The NoC eliminates the routing congestion issues common in large FPGAs. I recently worked on a 5G baseband project where the AI Engines handled massive MIMO processing while the PL managed the fronthaul interface. The 152 GTY transceivers at 58 Gbps enable 400G Ethernet and next-generation connectivity. Power consumption is significant at 40-60W, but the performance per watt is exceptional. This is not just an evolution of FPGA - it's a completely new compute platform that bridges the gap between fixed-function ASICs and programmable logic."
Revolutionary AI Engine architecture delivering 100x performance for ML workloads
— Dr. Sarah Johnson, BeiLuo
Frequently Asked Questions
How do I program the AI Engines?
AI Engine programming workflow: 1) Kernel development - write C/C++ kernels using AI Engine API, 2) Graph specification - define dataflow graph connecting kernels, 3) Compilation - use aiecompiler to generate ELF files, 4) Simulation - test in AI Engine simulator, 5) Integration - link with PL and host application. The programming model is similar to CUDA but optimized for dataflow. Vitis IDE provides integrated development environment.
Start with example designs. Use graph-based programming for dataflow applications.
What AI frameworks are supported?
Versal supports major AI frameworks: 1) TensorFlow - via Vitis AI quantizer and compiler, 2) PyTorch - supported through ONNX conversion, 3) Caffe - native support in Vitis AI, 4) ONNX - open standard for model exchange, 5) Custom - direct programming of AI Engines. Vitis AI provides optimized libraries for common operations. Model quantization required for INT8 inference.
Use Vitis AI for framework support. Quantize models to INT8 for best performance.
How does the NoC simplify system design?
NoC benefits for system design: 1) Bandwidth - guaranteed high bandwidth between engines, 2) Latency - predictable latency for real-time applications, 3) Connectivity - automatic connection of memory and engines, 4) QoS - quality of service for critical traffic, 5) Scalability - easy to add new connections. NoC eliminates manual routing and timing closure challenges. Software configuration at boot time.
Use NoC for all high-bandwidth connections. Configure QoS for real-time traffic.
What is the development flow for Versal?
Versal development flow: 1) Platform creation - define hardware platform in Vivado, 2) AI Engine development - create kernels and graph in Vitis, 3) PL development - design RTL or HLS for adaptable engine, 4) Host software - develop Linux application for A72, 5) Integration - link all components in Vitis. The flow is more complex than FPGA due to heterogeneous architecture.
Start with reference designs. Use platform-based development approach.
How do I migrate from FPGA to Versal?
FPGA to Versal migration considerations: 1) PL logic - largely portable with minor modifications, 2) AI Engine - new development for acceleration, 3) Processor - similar to Zynq MPSoC, 4) Memory - NoC replaces traditional memory controllers, 5) Tools - Vivado and Vitis with ACAP extensions. Plan for architecture redesign to leverage AI Engines. Not a simple port - requires rethinking the compute architecture.
Redesign compute architecture to leverage AI Engines. Plan significant development effort.