TL;DR: A study of the effects of adding two scan primitives as unit-time primitives to PRAM (parallel random access machine) models is presented and it is shown that the primitives improve the asymptotic running time of many algorithms by an O(log n) factor, greatly simplifying the description of many technologies.
Abstract: A study of the effects of adding two scan primitives as unit-time primitives to PRAM (parallel random access machine) models is presented. It is shown that the primitives improve the asymptotic running time of many algorithms by an O(log n) factor, greatly simplifying the description of many algorithms, and are significantly easier to implement than memory references. It is argued that the algorithm designer should feel free to use these operations as if they were as cheap as a memory reference. The author describes five algorithms that clearly illustrate how the scan primitives can be used in algorithm design: a radix-sort algorithm, a quicksort algorithm, a minimum-spanning-tree algorithm, a line-drawing algorithm, and a merging algorithm. These all run on an EREW (exclusive read, exclusive write) PRAM with the addition of two scan primitives and are either simpler or more efficient than their pure PRAM counterparts. The scan primitives have been implemented in microcode on the Connection Machine system, are available in PARIS (the parallel instruction set of the machine). >
TL;DR: This work presents a multi-scale layout algorithm for the aesthetic drawing of undirected graphs with straight-line edges that can significantly improve the speed of essentially any force-directed method (regardless of that method's ability of drawing weighted graphs or the continuity of its cost-function).
Abstract: We present a multi-scale layout algorithm for the aesthetic drawing of undirected graphs with straight-line edges. The algorithm is extremely fast, and is capable of drawing graphs of substantially larger size than any other algorithm we are aware of. For example, the algorithm achieves optimal drawings of 1000 vertex graphs in about 2 seconds. The paper contains graphs with over 6000 nodes. The proposed algorithm embodies a new multi-scale scheme for drawing graphs, which was motivated by the recently published multi-scale algorithm of Hadany and Harel [7]. It can significantly improve the speed of essentially any force-directed method (regardless of that method's ability of drawing weighted graphs or the continuity of its cost-function).
TL;DR: An iterative drawing algorithm for undirected graphs, based on a force-directed approach, that preserves edge crossing properties and describes applications of this technique to improve classical algorithms for drawing planar graphs and for interactive graph drawing.
TL;DR: In this paper an algorithm is developed based on the original Bresenham scan-conversion together with the symmetry first noted by Gardner [18] and a recent double-step technique that results in a speed-up of scan- Conversion by a factor of approximately 4.
Abstract: A major bottleneck in many graphics displays is the time required to scan-convert straight line segments. Most manufacturers use hardware based on Bresenham's [5] line algorithm. In this paper an algorithm is developed based on the original Bresenham scan-conversion together with the symmetry first noted by Gardner [18] and a recent double-step technique [31]. This results in a speed-up of scan-conversion by a factor of approximately 4 as compared to the original Bresenham algorithm. Hardware implementations are simple and efficient since the property of using only shift and increment operations is preserved.
TL;DR: In this paper, a modified integer Bresenham line-drawing algorithm that yields optimally accurate coverage values is presented. But this method requires the computation of an arithmetic division at each pixel.
Abstract: Described herein are a system and method for drawing high-quality, mathematically perfect or near-perfect anti-aliased lines by using a modified integer Bresenham line-drawing algorithm that yields optimally accurate coverage values. These coverage values are derived from the Bresenham algorithm itself without the computational expense of an arithmetic division at each pixel. The Bresenham algorithm generates pixel coordinates and coverage values of a line by iterating the line's minor axis coordinate with subpixel precision.