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Predictive performance modeling for distributed batch processing using black box monitoring and machine learning
In many domains, the previous decade was characterized by increasing data volumes and
growing complexity of data analyses, creating new demands for batch processing on …
growing complexity of data analyses, creating new demands for batch processing on …
Automated smartnic offloading insights for network functions
The gap between CPU and networking speeds has motivated the development of
SmartNICs for NF (network functions) offloading. However, offloading performance is …
SmartNICs for NF (network functions) offloading. However, offloading performance is …
Using automated performance modeling to find scalability bugs in complex codes
Many parallel applications suffer from latent performance limitations that may prevent them
from scaling to larger machine sizes. Often, such scalability bugs manifest themselves only …
from scaling to larger machine sizes. Often, such scalability bugs manifest themselves only …
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 …
A regression-based approach to scalability prediction
Many applied scientific domains are increasingly relying on large-scale parallel
computation. Consequently, many large clusters now have thousands of processors …
computation. Consequently, many large clusters now have thousands of processors …
Benchmarking machine learning methods for performance modeling of scientific applications
Performance modeling is an important and active area of research in high-performance
computing (HPC). It helps in better job scheduling and also improves overall performance of …
computing (HPC). It helps in better job scheduling and also improves overall performance of …
Phantom: predicting performance of parallel applications on large-scale parallel machines using a single node
For designers of large-scale parallel computers, it is greatly desired that performance of
parallel applications can be predicted at the design phase. However, this is difficult because …
parallel applications can be predicted at the design phase. However, this is difficult because …
Performance prediction of parallel applications: a systematic literature review
Different techniques for estimating the execution time of parallel applications have been
studied for the last 25 years. These approaches have proposed different methods for …
studied for the last 25 years. These approaches have proposed different methods for …
GROPHECY: GPU performance projection from CPU code skeletons
We propose GROPHECY, a GPU performance projection framework that can estimate the
performance benefit of GPU acceleration without actual GPU programming or hardware …
performance benefit of GPU acceleration without actual GPU programming or hardware …
[ספר][B] Parallel computing hits the power wall: principles, challenges, and a survey of solutions
AF Lorenzon, ACS Beck Filho - 2019 - books.google.com
This book describes several approaches to adaptability that are applied for the optimization
of parallel applications, such as thread-level parallelism exploitation and dynamic voltage …
of parallel applications, such as thread-level parallelism exploitation and dynamic voltage …