 
Summary: RealTime Parallel Hashing on the GPU
Dan A. Alcantara Andrei Sharf Fatemeh Abbasinejad Shubhabrata Sengupta Michael Mitzenmacher
John D. Owens
University of California, Davis
Nina Amenta
Harvard University
Figure 1: Overview of our construction for a voxelized Lucy model, colored by mapping x, y, and z coordinates to red, green, and blue
respectively (far left). The 3.5 million voxels (left) are input as 32bit keys and placed into buckets of 512 items, averaging 409 each
(center). Each bucket then builds a cuckoo hash with three subtables and stores them in a larger structure with 5 million entries (right).
Closeups follow the progress of a single bucket, showing the keys allocated to it (center; the bucket is linear and wraps around left to right)
and each of its completed cuckoo subtables (right). Finding any key requires checking only three possible locations.
Abstract
We demonstrate an efficient dataparallel algorithm for building
large hash tables of millions of elements in realtime. We consider
two parallel algorithms for the construction: a classical sparse per
fect hashing approach, and cuckoo hashing, which packs elements
densely by allowing an element to be stored in one of multiple pos
sible locations. Our construction is a hybrid approach that uses both
algorithms. We measure the construction time, access time, and
memory usage of our implementations and demonstrate realtime
