The document describes Xilinx's Vitis and Vitis AI platforms for application acceleration from cloud to edge, highlighting key challenges such as programming integration, retargetability, and efficient machine learning acceleration. It outlines a platform-based development approach, comprehensive development tools, open-source libraries, and various AI models for real-time inference. Additionally, it emphasizes participation in open-source standards and offers resources for further information.

1. © 2020 Xilinx
Vitis and Vitis AI:
Application Acceleration from
Cloud to Edge
Vinod Kathail
Fellow and Chief Architect SW Tools

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Industry Trends
Heterogeneous
Compute
Cloud to Edge AI Proliferation
Key challenge:
Programming &
integration of accelerators
Key challenge:
Need for retargetability
Key challenge:
Efficient ML acceleration and
integration in the whole application

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Heterogeneous
Compute
Cloud to Edge AI Proliferation

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Vitis Unified
Software Platform

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From Hardware to Software Programmable
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Vitis: Unified Software Platform

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Anatomy of an Accelerated Application
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AXI (or PCIe)
CPU
Host Application
Drivers
XRT
XRT/OpenCL API
FPGA
Accelerated Functions
DMA Engine
Global Memory
AXI Interfaces
User
Application
Code
Acceleration
Platform

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Platform-Based Development Approach
Development is performed in the context of a platform
• A pre-configured system containing I/O, status monitoring, and lifecycle management
Standardized interfaces allow for automated composition of user functionality

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Vitis: Comprehensive Development Tool Suite
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Build
Run
System level
Simulation
ARM
Compiler
AIE
Compiler
Vitis HLSHost CPU
System Compile/Link
Xilinx Runtime Library (XRT)
Device/Card Device/CardDevice/Card
Analyze
Host
Application Libraries
Application
C/C++
Target
PlatformRTL
Debug & Performance
Analysis

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Kernel Drivers
User Space Library
Kernel Drivers
OCL XMA AI C++ Python
XOCL ZOCL
Ultrascale
PCI-e Device
MPSoC/ACAP
PCI-e Device
MPSoC/
ACAP Device
MB scheduler ARM Scheduler ARM Scheduler
˃ Platform- and OS-independent APIs for
Device management
Memory management and data transfers
Accelerator execution management
˃ OpenCL wrappers, media frameworks,
and domain-specific APIs built on top of
base APIs
˃ Open source and available on GitHub
Xilinx Runtime (XRT)

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Open Source, Standards Based Libraries
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https://github.com/Xilinx/Vitis_Libraries
Vision & Image Finance Data Analytics &
Database
Data Compression Data Security
Math Linear Algebra Statistics DSP Data Management
Domain-Specific Libraries
Common Libraries
400+ functions across multiple libraries for performance-optimized out-of-the-box acceleration
Library
Docs
Tests
Examples
Bench-
marks

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Vitis Vision Libraries
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Deploy: Embedded, Single Server, Scale-out

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Vitis drivers & runtime (XRT)
Frameworks
Vitis AI
Development
Kit
Vitis AI
Models
DSA
AI Quantizer AI CompilerAI Optimizer AI Profiler
LSTM DPU MLP DPUCNN DPU
60+ pretrained, optimized
reference models
Performance
improvement up to 10-20x
Tensor based ISA for true
software programmability
DSA – Domain Specific Architecture
DPU – DNN Processing Unit
Vitis AI: Real Time AI Inference Acceleration

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ACAP
Server
CPU
PCI
Express
FPGA
AI Engine
CPU
Cores
Video Analytics
Management
Computer
Vision
Primary
Detector (AI)
Object
Tracker
Secondary
Classifiers (AI)
Video
Decode
AI Embedded in Apps, Rarely the Whole App

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Example: Whole Application Acceleration
>>
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Input
Image
2-3 days to integrate and test using Vitis and Vitis+AI Libraries
0
100
200
300
Tiny Yolo v3 Resnet-50 GoogleNet
Frames/sec
Speedup over CPU
CPU FPGA
Implemented either in FPGA or CPU Always in FPGA

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Example: Defect Detection
Low Latency: End-to-end < 250ms
>>
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Shell
Hardware
Developers
Application
Software Developers
AI and Data Scientists
(iterations in minutes)
Embedded
Developers
Putting it All Together

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Summary
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Unified Software Platform
 Cloud to edge, software and AI
 Comprehensive tools, runtime, libraries and models
Standards, Open Source
 Participating in open source
 Use of standard environments & APIs

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Additional Resources
Please visit the following sites for more information
Vitis Unified SW Platform
• https://www.xilinx.com/products/design-
tools/vitis.html
Vitis Libraries
• https://www.xilinx.com/products/design-
tools/vitis/vitis-libraries.html
• https://github.com/Xilinx/Vitis_Libraries/
Vitis AI
• https://www.xilinx.com/products/design-
tools/vitis/vitis-ai.html
Visit the Avnet-Xilinx booth to see the following demonstrations
in action:
• Face Detection, Pedestrian Detection, Pose Estimation,
Machine Learning and more
• Hardware families include the Zynq Ultrascale+ and Versal
AI Core
• Demonstration platforms include our SmartCamera+,
Ultra96, and UltraZed
• Xilinx and Avnet staff will be available to answer any
questions
2020 Embedded Vision Summit
• Vitis and Vitis AI: Application Acceleration from Cloud to
Edge
• September 17, 2020, 11:00-11:30AM PDT
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