Get Familiar with the Versal ACAP Architecture

July 29, 2021

Blog

Versal ACAP devices are used for a wide range of applications such as data center, Wireless 5G, AI/ML, A & D Radars, Automotive, and wired applications.

Overview

Xilinx’s new heterogeneous compute platform, Versal Adaptive Compute Acceleration Platform (ACAP), efficiently combines the power of software and hardware programmability.

Hardware Architecture

Versal ACAP is powered by scalable, adaptable, and Intelligent engines. On-chip memory access for all the machines is enabled via network on chip (NoC).

 

(Image Source: https://www.xilinx.com/products/silicon-devices/acap/versal-premium.html)

Scalar Engines

Scalar engines power platform computing, decision making, and control. For general-purpose computing, a dual-core ARM cortex- A72 Application Processing Unit (APU) is used in versal. APU supports virtualization, allowing multiple software stacks to run simultaneously. The dual core ARM cortex R5F Realtime Processing Unit (RPU) is available for real-time applications. RPU can be configured as a single/dual processor in lockstep mode. RPU can be used for variety of time-critical applications, e.g., safety in the automotive domain.

Platform Management Controller

Platform Management Controller (PMC) is responsible for boot, configuration, partial re-configuration, and general platform management tasks, including power, clock, pin control, reset management, and system monitoring. It is also responsible for device life cycle management, including security.

Adaptable Engines

The adaptable engines feature the classic FPGA technology - the programable silicon. Adaptable engines include DSP engines (Adaptable), configurable logic blocks (Intelligent), and two types of RAM (Block RAM and Ultra RAM (adaptable)). Using such a configurable structure, users can create any kind of accelerator for different kinds of applications.

Intelligent Engines

AI engines are software programmable and hardware adaptable. They are an array of VLIW SIMD vector processors used for ML/AI inference and advanced signal processing. The AI engine is tile-based architecture. Each tile is made of a vector processor, scaler processor, dedicated program and data memory, dedicated AXI data movement channels, DMA, and locks.

Network on Chip

Network on Chip (NoC) makes Versal ACAPs even more powerful by connecting all engines, memory hierarchy, and highspeed IOs. NoC makes each hardware component and soft IP modules accessible to each other and the software via a memory-mapped interface.

Software Support

Xilinx introduced Vitis – A unified software development platform that enables embedded software and accelerated applications on heterogeneous Xilinx platforms, including FPGAs, SoCs, and Versal ACAPs.

The Vitis unified software development platform provides sets of open-source libraries, enabling developers to build hardware-accelerated applications without hardware knowledge. It also provides Xilinx Runtime Library (XRT), including firmware, board utilities, kernel driver, user-space libraries, and APIs. Vitis also provides an AI development environment including deep learning frameworks like TensorFlow, PyTorch, and Caffe, and offers comprehensive APIs to prune, quantize, optimize, debug, and compile trained networks to achieve the highest AI inference performance.

 

(Image source: https://www.xilinx.com/products/design-tools/vitis/vitis-platform.html )

Softnautics is developing high-performance Vision & ML/AI solutions using Versal ACAP by utilizing high bandwidth and configurable NoC, AI engine tile array in tandem with DMA, and interconnect with PL. Versal’s high bandwidth interfaces and high compute processors can improve performance. One such use-case is Softnautics’ work in developing a Scene Text Detection solution using Vitis AI & DPU.

The Scene Text Detection use-case demands high compute power for LSTM operations. Our AI/ML engineers team evaluates their design to leverage the custom memory hierarchy and the multicast stream capability on AI interconnect and AI-optimized vector instructions to gain the best performance.

With a powerful AI Engine DMA capability and ping-pong buffering of stream data onto local tile memory, the ability of parallel processing opens a plethora of optimized implementations. Direct memory access (DMA) in the AI Engine tile moves data from the incoming stream(s) to local memory and from local memory to outgoing stream(s). Configuration interconnect (through memory-mapped AXI4 interface) with a shared, transaction-based, switched interconnect provides access from external masters to the internal AI Engine tile. Further, cascade streams across multiple AI Engine tiles allow for greater flexibility in design by accommodating multiple ML inference instances.

Softnautics has also been an early major contributor in Versal ACAP Platform Management-related developments. Some of the key contributions in this space involve developing software components on Versal, such as platform management library (xilpm), Arm Trusted Firmware, Linux device drivers, u-boot for Platform Management.

For more information, visit Softnautics.