Task scheduling in parallel and distributed systems
Task scheduling in parallel and distributed systems
Parallel application performance on shared, heterogeneous workstations
Parallel application performance on shared, heterogeneous workstations
Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
Reconfigurable computing: a survey of systems and software
ACM Computing Surveys (CSUR)
Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Genetic Algorithm for Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
A taxonomy of scheduling in general-purpose distributed computing systems
IEEE Transactions on Software Engineering
Application Load Imbalance on Parallel Processors
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Analytical modeling of high performance reconfigurable computers: prediction and analysis of system performance
Pilchard — A Reconfigurable Computing Platform with Memory Slot Interface
FCCM '01 Proceedings of the the 9th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Parallel application performance on shared high performance reconfigurable computing resources
Performance Evaluation - Performance modelling and evaluation of high-performance parallel and distributed systems
Software/Hardware Co-Scheduling for Reconfigurable Computing Systems
FCCM '07 Proceedings of the 15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
RAT: RC Amenability Test for Rapid Performance Prediction
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
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In the field of high-performance computing, systems harboring reconfigurable devices, such as field-programmable gate arrays (FPGAs), are gaining more widespread interest. Such systems range from supercomputers with tightly coupled reconfigurable hardware to clusters with reconfigurable devices at each node. The use of these architectures for scientific computing provides an alternative for computationally demanding problems and has advantages in metrics, such as operating cost/performance and power/performance. However, performance optimization of these systems can be challenging even with knowledge of the system’s characteristics. Our analytic performance model includes parameters representing the reconfigurable hardware, application load imbalance across the nodes, background user load, basic message-passing communication, and processor heterogeneity. In this article, we provide an overview of the analytical model and demonstrate its application for optimization and scheduling of high-performance reconfigurable computing (HPRC) resources. We examine cost functions for minimum runtime and other optimization problems commonly found in shared computing resources. Finally, we discuss additional scheduling issues and other potential applications of the model.