Whole Slide Images (WSI) in digital pathology routinely exceed 100,000 x 100,000 pixels at 40x magnification. Loading an entire tissue slide into GPU memory for transformer attention is mathematically impossible under standard hardware constraints. We present a sparse hierarchical attention pipeline that reduces GPU VRAM consumption by 65% while maintaining multi-instance learning performance.