Graphics Hardware

2019 ◽  
pp. 847-896
Keyword(s):  
2007 ◽  
Vol 34 (11) ◽  
pp. 4302-4308 ◽  
Author(s):  
Jakob Spoerk ◽  
Helmar Bergmann ◽  
Felix Wanschitz ◽  
Shuo Dong ◽  
Wolfgang Birkfellner
Keyword(s):  

Author(s):  
Timothy J. Purcell ◽  
Craig Donner ◽  
Mike Cammarano ◽  
Henrik Wann Jensen ◽  
Pat Hanrahan

2013 ◽  
Vol 21 (1) ◽  
Author(s):  
J. Lipowski

AbstractModern hardware accelerated graphics pipelines are designed to operate on data in a so called streaming model. To process the data in this model one needs to impose some restrictions on input and output argument’s (most frequently represented by a two-dimensional frame buffer) memory structure. The output data regularity is obvious when we consider rasterizing hardware architecture, which draws 3D polygons using depth buffer to resolve the visible surface problem. But recently the user’s needs surpass those restrictions with increasing frequency. In this work we formulate and present new methods of irregular frame buffer storage and ordering. The so called deque buffer (or D-buffer) allows us to decrease the amount of memory used for storage as well as the memory latency cost by using pixel data ordering. Our findings are confirmed by experimental results that measure the processing time, which is up to four times shorter, when compared with previous work by other authors. We also include a detailed description of algorithms used for D-buffer construction on the last three consumer-grade graphics hardware architectures, as a guide for other researchers and a development aid for practitioners. The only theoretical requirement imposed by our method is the use of memory model with linear address space.


2008 ◽  
Vol 08 (01) ◽  
pp. 81-98 ◽  
Author(s):  
NICOLAS COURTY ◽  
PIERRE HELLIER

There is an increasing need for real-time implementation of 3D image analysis processes, especially in the context of image-guided surgery. Among the various image analysis tasks, non-rigid image registration is particularly needed and is also computationally prohibitive. This paper presents a GPU (Graphical Processing Unit) implementation of the popular Demons algorithm using a Gaussian recursive filtering. Acceleration of the classical method is mainly achieved by a new filtering scheme on GPU which could be reused in or extended to other applications and denotes a significant contribution to the GPU-based image processing domain. This implementation was able to perform a non-rigid registration of 3D MR volumes in less than one minute, which corresponds to an acceleration factor of 10 compared to the corresponding CPU implementation. This demonstrated the usefulness of such method in an intra-operative context.


Sign in / Sign up

Export Citation Format

Share Document