Limoncello: Prefetchers for Scale
Akanksha Jain, Hannah Lin, Carlos Villavieja, Baris Kasikci, Chris Kennelly, Milad Hashemi, Parthasarathy Ranganathan
Abstract
This paper presents Limoncello, a novel software system that dynamically configures data prefetchers for high-utilization systems. We demonstrate that in resource-constrained environments, such as large data centers, traditional methods of hardware prefetching can increase memory latency and decrease available memory bandwidth. To address this issue, Limoncello disables hardware prefetchers when memory bandwidth utilization is high, and it leverages targeted software prefetching to reduce cache misses when hardware prefetchers are disabled. Limoncello is software-centric and does not require any modifications to hardware. Our evaluation of the deployment on Google's fleet reveals that Limoncello unlocks significant performance gains for high-utilization systems: It improves application throughput by 10%, due to a 15% reduction in memory latency, while maintaining minimal change in cache miss rate for targeted library functions.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Cited by top-tier papers4
- SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?Jeffrey Ma, Milad Hashemi, Amir Yazdanbakhsh, Kevin Swersky et al.ICML 2026 · 13 citations
- Micro-MAMA: Multi-Agent Reinforcement Learning for Multicore PrefetchingCharles Block, Gerasimos Gerogiannis, Josep TorrellasMICRO 2025 · 6 citations
- Harvesting Memory-bound CPU Stall Cycles in Software with MSHZhihong Luo, Sam Son, Sylvia Ratnasamy, Scott ShenkerOSDI 2024 · 5 citations
- FaScalSQL: A Fast and Scalable GPU-Accelerated SQL Query Engine for Out-of-Memory TablesChaemin Lim, Suhyun Lee, Jinwoo Choi, Kwanghyun Park et al.ICDE 2026
Related papers
- Ripple: Profile-Guided Instruction Cache Replacement for Data Center ApplicationsTanvir Ahmed Khan, Dexin Zhang, Akshitha Sriraman, Joseph Devietti et al.ISCA 2021 · 33 citations
- Integrating Prefetcher Selection with Dynamic Request Allocation Improves Prefetching EfficiencyMengming Li, Qijun Zhang, Yongqing Ren, Zhiyao XieHPCA 2025 · 6 citations
- Preventing Network Bottlenecks: Accelerating Datacenter Services with Hotspot-Aware Placement for Compute and StorageHamid Hajabdolali Bazzaz, Yingjie Bi, Weiwu Pang, Minlan Yu et al.NSDI 2025 · 3 citations
- PF-LLM: Large Language Model Hinted Hardware PrefetchingCeyu Xu, Xiangfeng Sun, Weihang Li, Chen Bai et al.ASPLOS 2026
- RPG2: Robust Profile-Guided Runtime Prefetch GenerationYuxuan Zhang, Nathan Sobotka, Soyoon Park, Saba Jamilan et al.ASPLOS 2024 · 11 citations
