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The channel switching rate is an important performance bottleneck for the actual exploitation of DSA in the LTE-A network.
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This external memory access latency incurred a significant performance bottleneck.
However, I/O has become a significant performance bottleneck when scaling up to thousands of processes.
With such increasing levels of parallelism, synchronization is set to become a major performance bottleneck and efficient support for synchronization an important design criterion.
When system does not perform as expected is referred as performance bottleneck.
In order to understand the behavior and performance bottleneck, knowledge of the network connectivity is crucial.
Experimental results show that (1) MCWT-SG-O can significantly outperform MCWT-C and MCWT-SG-C, especially on Kepler GPU, (2) MCWT-GC can further improve the performance but performance bottleneck exists when running multiple GPGPUs on one node, and (3) tuning an appropriate FFT radix is important to MCWT-SG-O.
Intercommunication between various modules is a major performance bottleneck.
This redundant simulation may represent a performance bottleneck.
Here, we refer to this observation as the performance bottleneck.
Flash calculations are a performance bottleneck of compositional flow simulations.
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