AbstractIn this paper, a refined deterministic sampling strategy is presented. It allows to improve the performance of deterministic sample-sort algorithms to the point that they can compete with their randomized counterparts. The method is illustrated by a detailed analysis for the cases of sorting on meshes and for sorting in external memory on a single processor machine
The Parallel Disks Model (PDM) has been proposed to alleviate the I/O bottleneck that arises in the ...
The Parallel Disks Model (PDM) has been proposed to alleviate the I/O bottle-neck that arises in the...
Abstract:- In this paper we would like to introduce an efficient variant of Bitonic sorting that can...
Sorting on interconnection networks has been solved `optimally'. However, the `lower-order' terms ar...
We demonstrate that parallel deterministic sample sort for many-core GPUs (GPU BUCKET SORT) is not o...
We introduce a new deterministic parallel sorting algorithm for distributed memory machines based on...
We demonstrate that parallel deterministic sample sort for many-core GPUs (GPU Bucket Sort) is not o...
We introduce a new deterministic parallel sorting algorithm based on the regular sampling approach...
Abstract. Sample sort, a generalization of quicksort that partitions the input into many pieces, is ...
There are several available generic sorting algorithms that are highly optimized and are provided as...
This paper provides an overview of lower and upper bounds for mesh-connected processor networks. Mos...
Many sorting algorithms that perform well on uniformly distributed data suffer significant performan...
In this paper1, we examine the problem of stochastic sorting, which is also known as sorting with er...
Previous schemes for sorting on general-purpose parallel machines have had to choose between poor lo...
Abstract. The Parallel Disks Model (PDM) has been proposed to al-leviate the I/O bottleneck that ari...
The Parallel Disks Model (PDM) has been proposed to alleviate the I/O bottleneck that arises in the ...
The Parallel Disks Model (PDM) has been proposed to alleviate the I/O bottle-neck that arises in the...
Abstract:- In this paper we would like to introduce an efficient variant of Bitonic sorting that can...
Sorting on interconnection networks has been solved `optimally'. However, the `lower-order' terms ar...
We demonstrate that parallel deterministic sample sort for many-core GPUs (GPU BUCKET SORT) is not o...
We introduce a new deterministic parallel sorting algorithm for distributed memory machines based on...
We demonstrate that parallel deterministic sample sort for many-core GPUs (GPU Bucket Sort) is not o...
We introduce a new deterministic parallel sorting algorithm based on the regular sampling approach...
Abstract. Sample sort, a generalization of quicksort that partitions the input into many pieces, is ...
There are several available generic sorting algorithms that are highly optimized and are provided as...
This paper provides an overview of lower and upper bounds for mesh-connected processor networks. Mos...
Many sorting algorithms that perform well on uniformly distributed data suffer significant performan...
In this paper1, we examine the problem of stochastic sorting, which is also known as sorting with er...
Previous schemes for sorting on general-purpose parallel machines have had to choose between poor lo...
Abstract. The Parallel Disks Model (PDM) has been proposed to al-leviate the I/O bottleneck that ari...
The Parallel Disks Model (PDM) has been proposed to alleviate the I/O bottleneck that arises in the ...
The Parallel Disks Model (PDM) has been proposed to alleviate the I/O bottle-neck that arises in the...
Abstract:- In this paper we would like to introduce an efficient variant of Bitonic sorting that can...
DOI
Add to ORKG