Fetch Me If You Can: Evaluating CPU Cache Prefetching and Its Reliability on High Latency Memory

Memory can be located close to a CPU, at remote sockets, or on devices connected via interconnects such as CXL or NVLink.A larger distance between memory and a core accessing the memory usually results in higher access latency.Software prefetching algorithms claim to hide memory access latencies by moving data to the CPU cache before a core accesses the data.In this work, we analyze to what extent software prefetching can hide increased memory access latencies.We evaluate these on seven systems, each offering different memory technologies and access latencies.We show that prefetching can increase performance by up to 2.6 and 2.8 for B + -Tree and binary search workloads.We find that CPU fill buffers, which track L1 cache misses, and a workload's memory intensity dictate how much access latency can be hidden.CPUs implement prefetches differently.We introduce microbenchmarks that identify concrete target cache and eviction strategies for different prefetch localities across x86 and ARM architectures.When the fill buffers are full, CPUs either drop prefetches or halt until all can be executed.We refer to these behaviors as weak and strong prefetching reliability.We introduce microbenchmarks identifying a CPU's reliability.When prefetching 8 KiB B + -Tree nodes, weak reliability achieves a speedup of 2 while strong reliability degrades performance with a slowdown of 2.5 for lookup workloads.

Authors

Institutions

Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1145/3736227.3736231
Citations
3
Primary Topic
Advanced Data Storage Technologies
Type
article
Field-Weighted Citation Impact
4.46

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fetch Me If You Can: Evaluating CPU Cache Prefetching and Its Reliability on High Latency Memory

Tilmann Rabl, Marcel Weisgut, Fabian Mahling
3 citations
Advanced Data Storage Technologies
4.46
article

Fetch Me If You Can: Evaluating CPU Cache Prefetching and Its Reliability on High Latency Memory

Tilmann Rabl, Marcel Weisgut, Fabian Mahling
article en
3 citations

Abstract

Memory can be located close to a CPU, at remote sockets, or on devices connected via interconnects such as CXL or NVLink.A larger distance between memory and a core accessing the memory usually results in higher access latency.Software prefetching algorithms claim to hide memory access latencies by moving data to the CPU cache before a core accesses the data.In this work, we analyze to what extent software prefetching can hide increased memory access latencies.We evaluate these on seven systems, each offering different memory technologies and access latencies.We show that prefetching can increase performance by up to 2.6 and 2.8 for B + -Tree and binary search workloads.We find that CPU fill buffers, which track L1 cache misses, and a workload's memory intensity dictate how much access latency can be hidden.CPUs implement prefetches differently.We introduce microbenchmarks that identify concrete target cache and eviction strategies for different prefetch localities across x86 and ARM architectures.When the fill buffers are full, CPUs either drop prefetches or halt until all can be executed.We refer to these behaviors as weak and strong prefetching reliability.We introduce microbenchmarks identifying a CPU's reliability.When prefetching 8 KiB B + -Tree nodes, weak reliability achieves a speedup of 2 while strong reliability degrades performance with a slowdown of 2.5 for lookup workloads.

Hasso Plattner Institute (DE)
European Commission, Deutsche Forschungsgemeinschaft
Affordable and clean energy
Openalex Percentile: Top 5%
Advanced Data Storage Technologies
4.46
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Fetch Me If You Can: Evaluating CPU Cache Prefetching and Its Reliability on High Latency Memory — Tilmann Rabl, Marcel Weisgut, et al. · (2025) | TGRS Research Map | TGRS