Online energy-efficient fair scheduling for heterogeneous multi-cores considering shared resource contention

B Salami, H Noori, M Naghibzadeh - The Journal of Supercomputing, 2022 - Springer
Heterogeneous multi-core processors (HMP) are dual-objective hardware platforms which
integrate both high-performance and low power consumption processors. Investigation of …

Lightweight ml-based runtime prefetcher selection on many-core platforms

ES Alcorta, M Madhav, S Tetrick, NJ Yadwadkar… - arXiv preprint arXiv …, 2023 - arxiv.org
Modern computer designs support composite prefetching, where multiple individual
prefetcher components are used to target different memory access patterns. However …

DRLCap: Runtime GPU Frequency Capping with Deep Reinforcement Learning

Y Wang, M Hao, H He, W Zhang, Q Tang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Power and energy consumption is the limiting factor of modern computing systems. As the
GPU becomes a mainstream computing device, power management for GPUs becomes …

[HTML][HTML] Dynamic power budget redistribution under a power cap on multi-application environments

L Costero, FD Igual, K Olcoz - Sustainable Computing: Informatics and …, 2023 - Elsevier
We present a two-level implementation of an infrastructure that allows performance
maximization under a power-cap on multi-application environments with minimal user …

Smart resource allocation of concurrent execution of parallel applications

VS da Silva, AGD Nogueira, EC de Lima… - Concurrency and …, 2023 - Wiley Online Library
Thread‐level parallelism (TLP) has been widely exploited to optimize computational
resource usage in high‐performance systems. However, as many applications do not scale …

DeepP: deep learning multi-program prefetch configuration for the IBM POWER 8

M Lurbe, J Feliu, S Petit, ME Gómez… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Current multi-core processors implement sophisticated hardware prefetchers, that can be
configured by application (PID), to improve the system performance. When running multiple …

Characterizing Machine Learning-Based Runtime Prefetcher Selection

ES Alcorta, M Madhav, R Afoakwa… - IEEE Computer …, 2024 - ieeexplore.ieee.org
Modern computer designs support composite prefetching, where multiple prefetcher
components are used to target different memory access patterns. However, multiple …

[PDF][PDF] Hardware Prefetching Tuning Method Based on Program Phase Behavior

L Huang, L Yan, T Wu - Journal of Circuits, Systems and …, 2024 - researchgate.net
Modern high-performance processor systems universally employ hardware prefetch engines
to address the “memory wall” issue. Nonetheless, prefetchers are typically activated with the …

Dynamic power budget redistribution under a power cap on multi-application environments

LM Costero Valero, FD Igual Peña, K Olcoz Herrero - 2023 - docta.ucm.es
We present a two-level implementation of an infrastructure that allows performance
maximization under a power-cap on multiapplication environments with minimal user …

Exploiting data locality in cache-coherent NUMA systems

I Sánchez Barrera - 2022 - upcommons.upc.edu
The end of Dennard scaling has caused a stagnation of the clock frequency in computers.
To overcome this issue, in the last two decades vendors have been integrating larger …