A survey of machine learning for computer architecture and systems
It has been a long time that computer architecture and systems are optimized for efficient
execution of machine learning (ML) models. Now, it is time to reconsider the relationship …
execution of machine learning (ML) models. Now, it is time to reconsider the relationship …
Pythia: A customizable hardware prefetching framework using online reinforcement learning
Past research has proposed numerous hardware prefetching techniques, most of which rely
on exploiting one specific type of program context information (eg, program counter …
on exploiting one specific type of program context information (eg, program counter …
A survey of machine learning applied to computer architecture design
DD Penney, L Chen - arXiv preprint arXiv:1909.12373, 2019 - arxiv.org
Machine learning has enabled significant benefits in diverse fields, but, with a few
exceptions, has had limited impact on computer architecture. Recent work, however, has …
exceptions, has had limited impact on computer architecture. Recent work, however, has …
The championship simulator: Architectural simulation for education and competition
Recent years have seen a dramatic increase in the microarchitectural complexity of
processors. This increase in complexity presents a twofold challenge for the field of …
processors. This increase in complexity presents a twofold challenge for the field of …
Hermes: Accelerating long-latency load requests via perceptron-based off-chip load prediction
R Bera, K Kanellopoulos… - 2022 55th IEEE/ACM …, 2022 - ieeexplore.ieee.org
Long-latency load requests continue to limit the performance of modern high-performance
processors. To increase the latency tolerance of a processor, architects have primarily relied …
processors. To increase the latency tolerance of a processor, architects have primarily relied …
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 …
{TLB; DR}: Enhancing {TLB-based} Attacks with {TLB} Desynchronized Reverse Engineering
Translation Lookaside Buffers, or TLBs, play a vital role in recent microarchitectural attacks.
However, unlike CPU caches, we know very little about the exact operation of these …
However, unlike CPU caches, we know very little about the exact operation of these …
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 …