Assuring predictable resources (processors, memory, storage) for applications running on the Grid is a critical factor for the success of the Grid for solving real-life problems. We extend the Globus Resource Management Architecture to provide metascheduling, co-scheduling and advance co-reservation of resources, and compare the proposed architecture with existing metascheduling solutions.
We develop a matrix transpose approach on the POWER7 architecture based on modeling the memory access latency and cache, and then designing the cache blocking, data alignment, and prefetching techniques that enhance performance.
We consider the problem of efficiently computing matrix transposes on the POWER7 architecture. We develop a matrix transpose algorithm that uses cache blocking, cache prefetching and data alignment. We model the POWER7 data cache and memory concurrency and use the model to predict the memory throughput of the proposed matrix transpose algorithm. The performance of our matrix transpose algorithm is up to five times higher than that of the dgetmo routine of the Engineering and Scientific Subroutine Library and is 2.5 times higher than that of the code generated by compiler-inserted prefetching. Numerical experiments indicate a good agreement between the predicted and the measured memory throughput.
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