ParaGraph: graph editor support for parallel programming environments
International Journal of Parallel Programming
The CODE 2.0 graphical parallel programming language
ICS '92 Proceedings of the 6th international conference on Supercomputing
Parallel program performance metrics: a comprison and validation
Proceedings of the 1992 ACM/IEEE conference on Supercomputing
Design patterns: elements of reusable object-oriented software
Design patterns: elements of reusable object-oriented software
A graphical development and debugging environment for parallel programs
Parallel Computing - Special issue: distributed and parallel systems: environments and tools
MILLIPEDE: easy parallel programming in available distributed environments
Software—Practice & Experience
IEEE Parallel & Distributed Technology: Systems & Technology
Parallel Programmer Productivity: A Case Study of Novice Parallel Programmers
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Patterns for parallel programming
Patterns for parallel programming
Amdahl's Law in the Multicore Era
Computer
Intel threading building blocks
Intel threading building blocks
D2STM: Dependable Distributed Software Transactional Memory
PRDC '09 Proceedings of the 2009 15th IEEE Pacific Rim International Symposium on Dependable Computing
The tao of parallelism in algorithms
Proceedings of the 32nd ACM SIGPLAN conference on Programming language design and implementation
DISC'06 Proceedings of the 20th international conference on Distributed Computing
| Hi-index | 0.00 |
Over the last few years, Parallelism has been gaining increasing importance and multicore processing is now common. Massification of parallelism is driving research and development of novel techniques to overcome current limits of Parallel Computing. However, the scope of parallelization research focuses mainly on ever-increasing performance and much still remains to be accomplished regarding improving productivity in the development of parallel software. This PhD research aims to develop methods and tools to dilute parallel programming complexity and enable non-expert programmer to fully benefit from a new generation of parallelism-driven programming platforms. Although much work remains to be done to reduce the skill requirements for parallel programming to become within reach of medium-skill programming workforces, it is our belief that this research will help bridge that gap.