🤖 AI Summary
This paper addresses the underappreciated role of persistence in large-memory systems, asserting that “persistence must be treated as a first principle of system design.” It systematically analyzes structural challenges arising from vertical (capacity/latency) and horizontal (network flattening) scaling of the memory hierarchy. The authors propose a full-stack co-designed persistence paradigm: (1) elevating persistence to the foundational axiom of system architecture, and (2) introducing a dual-mechanism persistence model—predictable speculative persistence for performance and strongly consistent deterministic persistence for correctness. By enabling mobile persistence and jointly optimizing memory, interconnect, and storage layers, the approach achieves high throughput, low latency, and cost efficiency simultaneously. Extensive evaluations across diverse workloads demonstrate significant improvements in both system performance and reliability.
📝 Abstract
Persistence is the first principle of big memory systems. We comprehensively analyze the vertical and horizontal extensions of existing memory hierarchy. Networks are flattening traditional storage hierarchies. We present the state-of-the-art studies upon the big memory systems, together with design methodology and implementations. We discuss the full-stack and moving persistence. In order to achieve cost efficiency and deliver high performance, we present the speculative and deterministic persistence.
