Enabling transparent acceleration of big data frameworks using heterogeneous hardware

M Xekalaki, J Fumero, A Stratikopoulos… - Proceedings of the …, 2022 - dl.acm.org
The ever-increasing demand for high performance Big Data analytics and data processing,
has paved the way for heterogeneous hardware accelerators, such as Graphics Processing …

FusionCL: A machine-learning based approach for OpenCL kernel fusion to increase system performance

YN Khalid, M Aleem, U Ahmed, R Prodan, MA Islam… - Computing, 2021 - Springer
Employing general-purpose graphics processing units (GPGPU) with the help of OpenCL
has resulted in greatly reducing the execution time of data-parallel applications by taking …

Improving Vectorization Heuristics in a Dynamic Compiler with Machine Learning Models

R Mosaner, G Barany, D Leopoldseder… - Proceedings of the 14th …, 2022 - dl.acm.org
Optimizing compilers rely on many hand-crafted heuristics to guide the optimization process.
However, the interactions between different optimizations makes their design a difficult task …

Optimizing performance and energy efficiency in massively parallel systems

R Nozal - 2022 - repositorio.unican.es
Heterogeneous systems are becoming increasingly relevant, due to their performance and
energy efficiency capabilities, being present in all types of computing platforms, from …

[图书][B] Challenges and techniques for transparent acceleration of unmodified Big Data applications

MN Xekalaki - 2022 - search.proquest.com
The ever-increasing demand for high-performance Big Data analytics and data processing
has paved the way for heterogeneous hardware accelerators, such as Graphics Processing …

[图书][B] Performance Optimisations for Heterogeneous Managed Runtime Systems

M Papadimitriou - 2021 - search.proquest.com
High demand for increased computational capabilities and power efficiency has resulted in
making commodity devices integrating diverse hardware resources. Desktops, laptops, and …