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README.md
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# FPGA Hardware Acceleration over PCIe
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## What This Is
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Multi-threaded Linux application + custom kernel driver + FPGA hardware design that accelerates Sobel edge detection on images. Demonstrates full-stack embedded systems engineering from RTL to application layer.
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![System Overview][system_overview]
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## Project Summary
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This project implements a **full-stack hardware acceleration platform** that offloads compute-intensive image processing tasks from a multi-threaded Linux application to custom FPGA accelerators connected via PCIe. The system demonstrates advanced concepts in **computer architecture, hardware-software co-design, parallel processing, and driver development**.
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### Key Achievement
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Successfully designed and implemented a multi-acceleration-group architecture supporting **concurrent hardware acceleration** for up to **16 simultaneous threads**, with intelligent resource scheduling and DMA-based data transfers.
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- **See [Engineering Challenges Solved](#engineering-challenges-solved)**
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## Technical Overview
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**Hardware (Xilinx Virtex-7 FPGA)**
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- 7 parallel acceleration units supporting up to 16 concurrent threads
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- Custom IP cores designed in C/C++ (Vivado HLS), synthesized to RTL
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- PCIe Gen2 x4 interface with DMA engines for high-throughput data transfer
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- Sobel filter accelerator processing up to 1080p images
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**Software (Linux)**
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- **Kernel driver**: PCIe device management, MSI interrupts, multi-thread resource scheduling
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- **User application**: pthreads, memory-mapped I/O, DMA buffer management
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- **MicroBlaze firmware**: FPGA system initialization
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---
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## Architecture Highlights
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```
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┌─────────────────────────────────────────┐
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│ Multi-threaded Application (pthreads) │
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└──────────────┬──────────────────────────┘
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│ ioctl(), mmap()
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┌──────────────▼──────────────────────────┐
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│ Kernel Driver (Resource Scheduler) │ ← Thread arbitration, DMA setup
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└──────────────┬──────────────────────────┘
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│ PCIe, MSI Interrupts
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┌──────────────▼──────────────────────────┐
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│ FPGA Hardware (7 Accel Groups) │ ← Parallel processing
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│ • Fetch/Send Schedulers (DMA) │
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│ • Sobel Filter Accelerators │
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│ • Interrupt Manager │
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└─────────────────────────────────────────┘
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```
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**Why 7 acceleration groups?**
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- 2 Direct-mode (PCIe → BRAM, low latency)
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- 4 Indirect-mode (PCIe → DDR3, higher throughput)
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- 1 Scatter-Gather (supports fragmented user memory)
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Each can process different images simultaneously with driver-managed scheduling.
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---
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## Engineering Challenges Solved
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**1. Multi-thread resource arbitration**
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16 threads competing for 7 hardware units → Implemented two scheduling policies (greedy, best-available) in kernel driver with per-thread state tracking
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**2. PCIe interrupt routing**
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Designed custom Interrupt Manager IP to map 7 accelerators to MSI vectors, coordinated with GPIO-triggered interrupts
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**3. Zero-copy DMA from userspace**
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Used `get_user_pages()` + scatter-gather tables for direct DMA to/from application buffers without memcpy overhead
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**4. Hardware-software timing correlation**
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FPGA global timer accessible via memory-mapped registers for nanosecond-precision performance analysis
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---
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## Results
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- **Throughput**: Supports 16 concurrent requests with linear scaling up to 7 threads
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- **Latency**: ~50-100 μs for VGA images (640x480)
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---
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## Quick Start
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```bash
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# Generate custom IPs (one-time)
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cd Hardware/Vivado_HLS_IPs/Sobel_Filter && vivado_hls run_hls.tcl
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# ... repeat for 8 other IPs
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# Build bitstream
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cd Hardware && vivado -source create_project.tcl
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# Flow → Generate Bitstream
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# Load driver & run
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cd Software/Linux_App_Driver
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make
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./make_device
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insmod xilinx_pci_driver.ko
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./ui image. bmp 100 16 1 10 # 100 iterations, 16 threads
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```
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---
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## Repository Structure
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```
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Hardware/Vivado_HLS_IPs/ 9 custom IP cores (C++ → RTL)
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Hardware/Vivado_Block_Design/ System integration (AXI, PCIe, DDR3)
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Software/Linux_App_Driver/ Kernel driver + test application
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Software/Microblaze_XSDK/ FPGA firmware
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```
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[system_overview]: /Images/system_overview.png "System Overview Diagram"
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