Abstract: Hierarchical depth culling is an important optimization, which is present in all modern high performance graphics processors. We present a novel culling algorithm based on a layered depth representation, with a per-sample mask indicating which layer each sample belongs to. Our algorithm is feed forward in nature in contrast to previous work, which rely on a delayed feedback loop. It is simple to implement and has fewer constraints than competing algorithms, which makes it easier to load-balance a hardware architecture. Compared to previous work our algorithm performs very well, and it will often reach over 90% of the efficiency of an optimal culling oracle. Furthermore, we can reduce bandwidth by up to 16% by compressing the hierarchical depth buffer.