Bouquet of instruction pointers: Instruction pointer classifier-based spatial hardware prefetching
S Pakalapati, B Panda - 2020 ACM/IEEE 47th Annual …, 2020 - ieeexplore.ieee.org
Hardware prefetching is one of the common off-chip DRAM latency hiding techniques.
Though hardware prefetchers are ubiquitous in the commercial machines and prefetching …
Though hardware prefetchers are ubiquitous in the commercial machines and prefetching …
Clip: Load criticality based data prefetching for bandwidth-constrained many-core systems
B Panda - Proceedings of the 56th Annual IEEE/ACM …, 2023 - dl.acm.org
Hardware prefetching is a latency-hiding technique that hides the costly off-chip DRAM
accesses. However, state-of-the-art prefetchers fail to deliver performance improvement in …
accesses. However, state-of-the-art prefetchers fail to deliver performance improvement in …
Micro-armed bandit: lightweight & reusable reinforcement learning for microarchitecture decision-making
G Gerogiannis, J Torrellas - Proceedings of the 56th Annual IEEE/ACM …, 2023 - dl.acm.org
Online Reinforcement Learning (RL) has been adopted as an effective mechanism in
various decision-making problems in microarchitecture. Its high adaptability and the ability to …
various decision-making problems in microarchitecture. Its high adaptability and the ability to …
Berti: an accurate local-delta data prefetcher
A Navarro-Torres, B Panda… - 2022 55th IEEE/ACM …, 2022 - ieeexplore.ieee.org
Data prefetching is a technique that plays a crucial role in modern high-performance
processors by hiding long latency memory accesses. Several state-of-the-art hardware …
processors by hiding long latency memory accesses. Several state-of-the-art hardware …
Managing prefetchers with deep reinforcement learning
We aim to reduce contention caused by multiple aggressive prefetchers on shared
resources (eg, LLC and memory bandwidth) with a multi-agent reinforcement learning …
resources (eg, LLC and memory bandwidth) with a multi-agent reinforcement learning …
Puppeteer: A random forest based manager for hardware prefetchers across the memory hierarchy
Over the years, processor throughput has steadily increased. However, the memory
throughput has not increased at the same rate, which has led to the memory wall problem in …
throughput has not increased at the same rate, which has led to the memory wall problem in …
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 …
prefetcher components are used to target different memory access patterns. However …
ZPP: a dynamic technique to eliminate cache pollution in NoC based MPSoCs
Data prefetching efficiently reduces the memory access latency in NUCA architectures as
the Last Level Cache (LLC) is shared and distributed across multiple cores. But cache …
the Last Level Cache (LLC) is shared and distributed across multiple cores. But cache …
A prefetch control strategy based on improved hill-climbing method in asymmetric multi-core architecture
J Fang, Y Xu, H Kong, M Cai - The Journal of Supercomputing, 2023 - Springer
Cache prefetching is a traditional way to reduce memory access latency. In multi-core
systems, aggressive prefetching may harm the system. In the past, prefetching throttling …
systems, aggressive prefetching may harm the system. In the past, prefetching throttling …
A prefetch-adaptive intelligent cache replacement policy based on machine learning
Hardware prefetching and replacement policies are two techniques to improve the
performance of the memory subsystem. While prefetching hides memory latency and …
performance of the memory subsystem. While prefetching hides memory latency and …