This paper exploits parallel computing power of graphics cards to accelerate state space search. We illustrate that modern graphics processing units (GPUs) have the potential to speed up breadth-first search significantly. For a bitvector representation of the search frontier, GPU algorithms with one and two bits per state are presented. Efficient perfect hash functions and their inverse are explored in order to achieve enhanced compression. We report maximal speed-ups of up to a factor of 27 wrt. single core CPU computation
Since users rely on passwords to authenticate themselves to computer systems, ad-versaries attempt t...
Designing parallel models that fully utilize the computation capabilities of Graphics Processing Uni...
For appropriate matrix ensembles, greedy algorithms have proven to be an efficient means of solving ...
Exhaustive search is generally a last resort for solving a problem: each possible state of a system ...
In this paper optimal state space planning is parallelized by exploiting the processing power of a g...
We demonstrate an efficient data-parallel algorithm for building large hash tables of millions of el...
\u3cp\u3eIn the past few years, General Purpose Graphics Processors (GPUs) have been used to signifi...
A* search is a fundamental topic in artificial intelligence. Recently, the general purpose computat...
Data management systems commonly use bitmap indices to increase the efficiency of querying scientifi...
Data management systems commonly use bitmap indices to increase the efficiency of querying scientifi...
General purpose graphical processing units were proven to be useful for accelerating computationally...
The parallel computing power offered by graphic processing units (GPUs) has been recently exploited ...
Abstract—Optimized GPU kernels are sufficiently complicated to write that they often are specialized...
[[abstract]]Graphics processing units (GPUs) have attracted a lot of attention due to their cost-eff...
these pixels are shown as colors in (b). We store the image in a hash table under a 0.99 load factor...
Since users rely on passwords to authenticate themselves to computer systems, ad-versaries attempt t...
Designing parallel models that fully utilize the computation capabilities of Graphics Processing Uni...
For appropriate matrix ensembles, greedy algorithms have proven to be an efficient means of solving ...
Exhaustive search is generally a last resort for solving a problem: each possible state of a system ...
In this paper optimal state space planning is parallelized by exploiting the processing power of a g...
We demonstrate an efficient data-parallel algorithm for building large hash tables of millions of el...
\u3cp\u3eIn the past few years, General Purpose Graphics Processors (GPUs) have been used to signifi...
A* search is a fundamental topic in artificial intelligence. Recently, the general purpose computat...
Data management systems commonly use bitmap indices to increase the efficiency of querying scientifi...
Data management systems commonly use bitmap indices to increase the efficiency of querying scientifi...
General purpose graphical processing units were proven to be useful for accelerating computationally...
The parallel computing power offered by graphic processing units (GPUs) has been recently exploited ...
Abstract—Optimized GPU kernels are sufficiently complicated to write that they often are specialized...
[[abstract]]Graphics processing units (GPUs) have attracted a lot of attention due to their cost-eff...
these pixels are shown as colors in (b). We store the image in a hash table under a 0.99 load factor...
Since users rely on passwords to authenticate themselves to computer systems, ad-versaries attempt t...
Designing parallel models that fully utilize the computation capabilities of Graphics Processing Uni...
For appropriate matrix ensembles, greedy algorithms have proven to be an efficient means of solving ...