The need to rank and order data is pervasive, and many algorithms are fundamentally
dependent upon sorting and partitioning operations. Prior to this work, GPU stream …

This poster presents efficient strategies for sorting large sequences of fixed-length keys (and
values) using GPGPU stream processors. Compared to the state-of-the-art, our radix sorting …

The growing interest in GPU programming has brought renewed attention to the Single
Instruction Multiple Data (SIMD) execution model. SIMD machines give application …

Scan (also known as prefix sum) is a very useful primitive for various important parallel
algorithms, such as sort, BFS, SpMV, compaction and so on. Current state of the art of GPU …

GPUs have become a mainstream accelerator for database operations such as sorting. Most
GPU sorting algorithms are single-GPU approaches. They neither harness the full …

Parallel sorting algorithms are widely studied nowadays. After the introduction of parallel
processors such as graphics processing unit (GPU) and easy to use parallel programming …

We design a high-performance parallel merge sort for highly parallel systems. Our merge
sort is designed to use more register communication (not shared memory), and does not …

Sorting data is needed in many application domains. Traditionally, the data is read from
memory and sent to a general-purpose processor or application-specific hardware for …

Finding the k th-largest value in a list of n values is a well-studied problem for which many
algorithms have been proposed. A naïve approach is to sort the list and then simply select …

In this paper, we propose a novel sorting algorithm that sorts input data integer elements on-
the-fly without any comparison operations between the data-comparison-free sorting. We …