Presentation
Hydrogen: Contention-Aware Hybrid Memory Management for Heterogeneous CPU-GPU Architectures
DescriptionIntegrating hybrid memories with heterogeneous processors could leverage heterogeneity in both compute and memory domains for better system efficiency.
To ensure performance isolation, we introduce Hydrogen, a novel hardware architecture to optimize the allocation of hybrid memory resources to heterogeneous CPU-GPU systems.
Hydrogen supports efficient capacity and bandwidth partitioning between CPUs and GPUs in both memory tiers.
We propose decoupled memory channel mapping and token-based data migration throttling to enable flexible partitioning. We also support epoch-based online search for optimized configurations and lightweight reconfiguration with reduced data movements.
Hydrogen significantly outperforms existing designs by up to 1.31x.
To ensure performance isolation, we introduce Hydrogen, a novel hardware architecture to optimize the allocation of hybrid memory resources to heterogeneous CPU-GPU systems.
Hydrogen supports efficient capacity and bandwidth partitioning between CPUs and GPUs in both memory tiers.
We propose decoupled memory channel mapping and token-based data migration throttling to enable flexible partitioning. We also support epoch-based online search for optimized configurations and lightweight reconfiguration with reduced data movements.
Hydrogen significantly outperforms existing designs by up to 1.31x.
Event Type
Work-in-Progress Poster
TimeWednesday, June 265:00pm - 6:00pm PDT
LocationLevel 2 Lobby
AI
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