Development of Windows PCIe Software Stack for a Leading AI Accelerator Provider
Windows PCIe Software Stack for Enterprise AI Acceleration
Client
AI accelerator providers Semiconductor companies
Industry
Semiconductor Technology
Edge AI
Service
PCIe software development
Windows driver integration
Use Case
AI workload acceleration Industrial defect detection
Technology
PCIe Gen 5
GStreamer
Goal
Develop a production ready Windows PCIe Software Stack for a proprietary AI accelerator platform to enable seamless communication between accelerator hardware and Windows systems. The solution aimed to deliver high performance AI workload execution, simplified deployment, and compatibility with enterprise Windows environments while maintaining parity with the Linux reference implementation.
Problem Statement
The client’s PCIe host software stack was originally designed for Linux platforms, limiting adoption among enterprise users operating on Windows environments. Porting the stack to Windows introduced complex technical challenges including kernel level driver development, Microsoft Secure Boot compliance, high throughput PCIe communication, multi-layer software integration, and reliable synchronization between drivers, libraries, and user applications for real time AI processing workloads.
Solution Highlights
Vedya engineered a modular Windows PCIe Software Stack designed for scalable AI acceleration and optimized data processing workflows.
Kernel Level PCIe Driver Development
Developed a Windows PCIe device driver supporting PCIe Gen 4 and Gen 5 interfaces with MSI X, MSI, and legacy interrupt handling for reliable hardware communication
PCIe Host Middleware Layer
Built PCIeHostLib APIs enabling low latency communication, queue management, device configuration, and accelerator control operations
C ++ Integration Libraries
Designed higher level C Plus Plus libraries to simplify integration of AI and computer vision applications with accelerator hardware
Management and Deployment Agent
Implemented a management agent for device discovery, AI model deployment, runtime orchestration, and concurrent multi stream processing
Real Time Vision Pipeline Integration
Developed GStreamer plugin libraries enabling real time image analytics and multi camera inference workflows through PCIe based acceleration
Automated Build and Validation Infrastructure
Established CI CD workflows using Jenkins, Bitbucket Git, Python 3 automation scripts, and MSI based deployment packages for streamlined testing and delivery
Industrial AI Validation Use Case
Validated the platform using a YOLOv8 based defect detection model for industrial quality inspection on casting iron plates
Conclusion
Vedya successfully delivered a scalable and secure Windows PCIe Software Stack that expanded the client’s AI accelerator ecosystem beyond Linux platforms. The solution enabled high-performance AI inference, simplified model deployment, improved cross platform accessibility, and strengthened enterprise adoption across Windows based AI environments.