Performance prediction of deep learning applications training in GPU as a service systems

M Lattuada, E Gianniti, D Ardagna, L Zhang - Cluster Computing, 2022 - Springer
Data analysts predict that the GPU as a service (GPUaaS) market will grow to support 3D
models, animated video processing, gaming, and deep learning model training. The main …

AI-driven performance modeling for AI inference workloads

M Sponner, B Waschneck, A Kumar - Electronics, 2022 - mdpi.com
Deep Learning (DL) is moving towards deploying workloads not only in cloud datacenters,
but also to the local devices. Although these are mostly limited to inference tasks, it still …

An accurate model to predict the performance of graphical processors using data mining and regression theory

M Shafiabadi, H Pedram, M Reshadi, A Reza - Computers & Electrical …, 2021 - Elsevier
Nowadays the use of graphical processors in fast and accurate scientific calculations has
increased. The heterogeneous design space that is conducted by the processors could …

SDAM: a combined stack distance-analytical modeling approach to estimate memory performance in GPUs

M Kiani, A Rajabzadeh - The Journal of Supercomputing, 2021 - Springer
Graphics processing units (GPUs) are powerful in performing data-parallel applications.
Such applications most often rely on the GPU's memory hierarchy to deliver high …

Toward a general framework for jointly processor-workload empirical modeling

H Sheidaeian, O Fatemi - The Journal of Supercomputing, 2021 - Springer
The complexity of state-of-the-art processor architectures and their consequent vast design
spaces have made it difficult and time-consuming to explore the best configuration for them …