A common schema for dynamic programming and branch and bound algorithms
Journal of the ACM (JACM)
Guest editorial: Heterogeneous computing
Parallel Computing - Heterogeneous computing
Parallel Computing - Heterogeneous computing
Self-adapting numerical software (SANS) effort
IBM Journal of Research and Development
SuperMatrix: a multithreaded runtime scheduling system for algorithms-by-blocks
Proceedings of the 13th ACM SIGPLAN Symposium on Principles and practice of parallel programming
A performance study of general-purpose applications on graphics processors using CUDA
Journal of Parallel and Distributed Computing
Dynamic Load Balancing on Dedicated Heterogeneous Systems
Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
An Extension of the StarSs Programming Model for Platforms with Multiple GPUs
Euro-Par '09 Proceedings of the 15th International Euro-Par Conference on Parallel Processing
Rodinia: A benchmark suite for heterogeneous computing
IISWC '09 Proceedings of the 2009 IEEE International Symposium on Workload Characterization (IISWC)
On the Robust Mapping of Dynamic Programming onto a Graphics Processing Unit
ICPADS '09 Proceedings of the 2009 15th International Conference on Parallel and Distributed Systems
A Dynamic Programming Decomposition Method for Making Overbooking Decisions Over an Airline Network
INFORMS Journal on Computing
GPU parallelization of algebraic dynamic programming
PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part II
Dense Dynamic Programming on Multi GPU
PDP '11 Proceedings of the 2011 19th International Euromicro Conference on Parallel, Distributed and Network-Based Processing
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Actual HPC systems are composed by multicore processors and powerful graphics processing units. Adapting existing code and libraries to these new systems is a fundamental problem due to the important increment on programming difficulties. The heterogeneity, both at architectural and programming levels at the same time, raises the programmability wall. The performance of the code is affected by the large interdependence between the code and the parallel architecture. We have developed a dynamic load balancing library that allows parallel code to be adapted to a wide variety of heterogeneous systems. The overhead introduced by our system is minimal and the cost to the programmer negligible. This system has been successfully applied to solve load imbalance problems appearing in homogeneous and heterogeneous multiGPU platforms. We consider the Dynamic Programming technique as case of study to validate our proposals using different heterogeneous scenarios in multiGPU systems.