Enabling parallel simulation of large-scale HPC network systems
With the increasing complexity of today's high-performance computing (HPC) architectures,
simulation has become an indispensable tool for exploring the design space of HPC …
simulation has become an indispensable tool for exploring the design space of HPC …
Methods of inference and learning for performance modeling of parallel applications
Increasing system and algorithmic complexity combined with a growing number of tunable
application parameters pose significant challenges for analytical performance modeling. We …
application parameters pose significant challenges for analytical performance modeling. We …
An approach to performance prediction for parallel applications
Accurately modeling and predicting performance for large-scale applications becomes
increasingly difficult as system complexity scales dramatically. Analytic predictive models …
increasingly difficult as system complexity scales dramatically. Analytic predictive models …
Quantifying locality in the memory access patterns of HPC applications
J Weinberg, MO McCracken… - SC'05: Proceedings …, 2005 - ieeexplore.ieee.org
Several benchmarks for measuring the memory performance of HPC systems along
dimensions of spatial and temporal memory locality have recently been proposed. However …
dimensions of spatial and temporal memory locality have recently been proposed. However …
A simple approximation for modeling nonstationary queues
WP Wang, D Tipper, S Banerjee - Proceedings of IEEE …, 1996 - ieeexplore.ieee.org
Evaluation of the behavior of queues with nonstationary arrival processes is of importance in
several applications including communication networks. However, the analysis of …
several applications including communication networks. However, the analysis of …
Resource requests prediction in the cloud computing environment with a deep belief network
Accurate resource requests prediction is essential to achieve optimal job scheduling and
load balancing for cloud Computing. Existing prediction approaches fall short in providing …
load balancing for cloud Computing. Existing prediction approaches fall short in providing …
MUSA: a multi-level simulation approach for next-generation HPC machines
T Grass, C Allande, A Armejach, A Rico… - SC'16: Proceedings …, 2016 - ieeexplore.ieee.org
The complexity of High Performance Computing (HPC) systems is increasing in the number
of components and their heterogeneity. Interactions between software and hardware involve …
of components and their heterogeneity. Interactions between software and hardware involve …
Exploiting mean field analysis to model performances of big data architectures
Big data processing systems are characterized by a relevant number of components that are
used in parallel to run multiple instances of the same tasks in order to achieve the needed …
used in parallel to run multiple instances of the same tasks in order to achieve the needed …
Predicting parallel application performance via machine learning approaches
Consistently growing architectural complexity and machine scales make the creation of
accurate performance models for large‐scale applications increasingly challenging …
accurate performance models for large‐scale applications increasingly challenging …
ExaSAT: An exascale co-design tool for performance modeling
One of the emerging challenges to designing HPC systems is understanding and projecting
the requirements of exascale applications. In order to determine the performance …
the requirements of exascale applications. In order to determine the performance …