Hash tables are a fundamental data structure for effectively storing and accessing sparse
data, with widespread usage in domains ranging from computer graphics to machine …

For large-scale graph analytics on the GPU, the irregularity of data access and control flow,
and the complexity of programming GPUs, have presented two significant challenges to …

We design and implement a fully concurrent dynamic hash table for GPUs with comparable
performance to the state of the art static hash tables. We propose a warp-cooperative work …

Hash tables are ubiquitous. Properties such as an amortized constant time complexity for
insertion and querying as well as a compact memory layout make them versatile associative …

Many applications in computational sciences and social sciences exploit sparsity and
connectivity of acquired data. Even though many parallel sparse primitives such as sparse …

We present Onesweep, a least-significant digit (LSD) radix sorting algorithm for large GPU
sorting problems residing in global memory. Our parallel algorithm employs a method of …

We develop a dynamic dictionary data structure for the GPU, supporting fast insertions and
deletions, based on the Log Structured Merge tree (LSM). Our implementation on an NVIDIA …

We introduce coroutines into GPU kernel programming, providing an automated solution for
flexible splitting and scheduling of rendering tasks. This approach addresses a prevalent …

Hash maps are among the most versatile data structures in computer science because of
their compact data layout and expected constant time complexity for insertion and querying …

This paper presents a new Single Source Shortest Path (SSSP) algorithm for GPUs. Our key
advancement is an improved work scheduler, which is central to the performance of SSSP …