Image algebra techniques for parallel image processing
Journal of Parallel and Distributed Computing
An introduction to splines for use in computer graphics & geometric modeling
An introduction to splines for use in computer graphics & geometric modeling
A bridging model for parallel computation
Communications of the ACM
Efficiently computing static single assignment form and the control dependence graph
ACM Transactions on Programming Languages and Systems (TOPLAS)
Imaging vector fields using line integral convolution
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Software—Practice & Experience
Shrinking lambda expressions in linear time
Journal of Functional Programming
Curvature-Based Transfer Functions for Direct Volume Rendering: Methods and Applications
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Robust Particle Systems for Curvature Dependent Sampling of Implicit Surfaces
SMI '05 Proceedings of the International Conference on Shape Modeling and Applications 2005
Scout: a data-parallel programming language for graphics processors
Parallel Computing
Language virtualization for heterogeneous parallel computing
Proceedings of the ACM international conference on Object oriented programming systems languages and applications
Liszt: a domain specific language for building portable mesh-based PDE solvers
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
A Heterogeneous Parallel Framework for Domain-Specific Languages
PACT '11 Proceedings of the 2011 International Conference on Parallel Architectures and Compilation Techniques
API compilation for image hardware accelerators
ACM Transactions on Architecture and Code Optimization (TACO) - Special Issue on High-Performance Embedded Architectures and Compilers
Composition and reuse with compiled domain-specific languages
ECOOP'13 Proceedings of the 27th European conference on Object-Oriented Programming
| Hi-index | 0.00 |
Research scientists and medical professionals use imaging technology, such as computed tomography (CT) and magnetic resonance imaging (MRI) to measure a wide variety of biological and physical objects. The increasing sophistication of imaging technology creates demand for equally sophisticated computational techniques to analyze and visualize the image data. Analysis and visualization codes are often crafted for a specific experiment or set of images, thus imaging scientists need support for quickly developing codes that are reliable, robust, and efficient. In this paper, we present the design and implementation of Diderot, which is a parallel domain-specific language for biomedical image analysis and visualization. Diderot supports a high-level model of computation that is based on continuous tensor fields. These tensor fields are reconstructed from discrete image data using separable convolution kernels, but may also be defined by applying higher-order operations, such as differentiation (∇). Early experiments demonstrate that Diderot provides both a high-level concise notation for image analysis and visualization algorithms, as well as high sequential and parallel performance.