Latency optimization for image processing pipelines on FPGAs using HLS
Let’s dive deeper into latency optimization for image processing pipelines on FPGAs using HLS. This is critical for real-time applications like video processing, autonomous vehicles, or medical imaging. Key Challenges in Image Processing HLS Designs High Data Volume : Pixels must be processed at low latency (e.g., <16.7 ms/frame for 60 FPS ). Memory Bottlenecks : Off-chip DDR access can dominate latency. Dependency Chains : Sequential operations (e.g., filters) introduce delays. Step-by-Step Latency Optimization Techniques 1. Algorithm-Level Optimizations A. Window Buffering (Line Buffers) Instead of processing entire frames, use sliding windows (e.g., 3×3 kernels for convolution). Reduces off-chip memory accesses by caching neighboring pixels in on-chip BRAM. cpp # pragma HLS ARRAY_PARTITION variable = line_buffer complete dim = 1 for ( int y = 0 ; y < height ; y ++ ) { for ( int x = 0 ; x < width ; x ++ )...