A New Formulation of Neural Data Prefetching

Temporal data prefetchers have the potential to produce significant performance gains by prefetching irregular data streams. Recent work has introduced a neural model for temporal prefetching that outperforms practical table-based temporal prefetchers, but the large storage and latency costs, along...

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Veröffentlicht in:	2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA) S. 1173 - 1187
Hauptverfasser:	Duong, Quang, Jain, Akanksha, Lin, Calvin
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 29.06.2024
Schlagworte:	Adaptation models Caches Costs Data Prefetching Irregular Temporal Prefetching Neural networks Prefetching Quantization (signal) Training Training data
Online-Zugang:	Volltext
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