Douglas Santry

GCTrees: Garbage Collecting Snapshots

File-system snapshots have been a key component of enterprise storage management since their inception. Creating and managing them efficiently, while maintaining flexibility and low overhead, has been a constant struggle. Although the current state-of-the-art mechanism—hierarchical reference counting—performs reasonably well for traditional small-file workloads, these workloads are increasingly vanishing from the enterprise data center, replaced instead with virtual machine and database workloads. These workloads center around a few very large files, violating the assumptions that allow hierarchical reference counting to operate efficiently. To better cope with these workloads, we introduce Generational Chain Trees (GCTrees), a novel method of space management that uses concepts of block lineage across snapshots rather than explicit reference counting. As a proof of concept, we create a prototype file system—gcext4, a modified version of ext4 that uses GCTrees as a basis for snapshots and copy-on-write. In evaluating this prototype empirically, we find that although they have a somewhat higher overhead for traditional workloads, GCTrees have dramatically lower overhead than hierarchical reference counting for large-file workloads, improving by a factor of 34 or more in some cases. Furthermore, gcext4 performs comparably to ext4 across all workloads, showing that GCTrees impose minor cost for their benefits.

GCTrees: Garbage collecting snapshots

File-system snapshots have been a key component of enterprise storage management since their inception. Creating and managing them efficiently, while maintaining flexibility and low overhead, has been a constant struggle. Although the current state-of-the-art mechanism, hierarchical reference counting, performs reasonably well for traditional small-file workloads, these workloads are increasingly vanishing from the enterprise data center, replaced instead with virtual machine and database workloads. These workloads center around a few very large files, violating the assumptions that allow hierarchical reference counting to operate efficiently. To better cope with these workloads, we introduce GCTrees, a novel method of space management that uses concepts of block lineage across snapshots, rather than explicit reference counting. As a proof of concept, we create a prototype file system, gcext4, a modified version of ext4 that uses GCTrees as a basis for snapshots and copy-on-write. In evaluating this prototype analytically, we find that, though they have a somewhat higher overhead for traditional workloads, GCTrees have dramatically lower overhead than hierarchical reference counting for large-file workloads, improving by a factor of 34 or more in some cases. Furthermore, gcext4 performs comparably to ext4 across all workloads, showing that GCTrees impose minor cost for their benefits.

PASTE: Network Stacks Must Integrate with NVMM Abstractions

This paper argues that the lack of explicit support for non-volatile main memory (NVMM) in network stacks fundamentally limits application performance. NVMM devices have been integrated into general-purpose OSes by providing familiar file-based interfaces and efficient byte-granularity access by bypassing page caches. However, this powerful property cannot be fully utilized unless network stacks also support it and applications exploit such support. This requires a thoroughly new network stack design, including low-level buffer management and APIs. We propose such a new network stack architecture to support NVMM and demonstrate its advantages for efficient write-ahead logging, a popular technique to implement transactions.