Computer-assisted microanalysis of parallel programs
ACM Transactions on Programming Languages and Systems (TOPLAS)
ICSE '76 Proceedings of the 2nd international conference on Software engineering
Parallel Programmer Productivity: A Case Study of Novice Parallel Programmers
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Understanding the Parallel Programmer
HPCS '06 Proceedings of the 20th International Symposium on High-Performance Computing in an Advanced Collaborative Environment
Computer
Why Johnny can't encrypt: a usability evaluation of PGP 5.0
SSYM'99 Proceedings of the 8th conference on USENIX Security Symposium - Volume 8
Parallel Programmability and the Chapel Language
International Journal of High Performance Computing Applications
Learning from mistakes: a comprehensive study on real world concurrency bug characteristics
Proceedings of the 13th international conference on Architectural support for programming languages and operating systems
Application Resilience: Making Progress in Spite of Failure
CCGRID '08 Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid
A pilot study to compare programming effort for two parallel programming models
Journal of Systems and Software
A view of the parallel computing landscape
Communications of the ACM - A View of Parallel Computing
Is transactional programming actually easier?
Proceedings of the 15th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
Mining problem-solving strategies from HCI data
ACM Transactions on Computer-Human Interaction (TOCHI)
A strategy-centric approach to the design of end-user debugging tools
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Workshop on transitioning to multicore (TMC 2011): overview abstract
Proceedings of the compilation of the co-located workshops on DSM'11, TMC'11, AGERE!'11, AOOPES'11, NEAT'11, & VMIL'11
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Multiprocessors are now commonplace, and cloud computing is swiftly following suit. While it is possible to write high performance code for these systems, concurrency bugs are extremely common and theoretical performance is often difficult to realize. In order to take advantage of increasing numbers of parallel resources, numerous parallel programming systems have been proposed and deployed, usually without a systematic evaluation of their usability. In order to make both programmers and their parallel applications more effective, we need more useful metrics for measuring programmer productivity and a better way to evaluate such metrics. We posit that usability is a key factor in the effectiveness of a parallel programming system, and that theoretical performance gains can only be realized if programmers are able to successfully reason about their parallel code.