Active-standby mechanisms for VM high-availability demand frequent synchronization of memory and CPU state, involving the identification and transfer of "dirty" memory pages to a standby target. Building upon the granularity offered by CXL-enabled memory devices, as discussed by Waddington et al. [21], this paper proposes a dictionary-based compression method operating on 64-byte cache lines to minimize snapshot volume and synchronization latency. The method aims to transmit only necessary information required to reconstruct the memory state at the standby machine, augmented by byte grouping and cache-line partitioning techniques. We assess the compression benefits on memory access patterns across 20 benchmarks snapshots and compare our approach to standard off-the-shelf compression methods. Our findings reveal significant improvements across nearly all benchmarks, with some experiencing over a twofold enhancement compared to standard compression, while others show more moderate gains. We conduct an in-depth experimental analysis on the contribution of each method and examine the nature of the benchmarks. We ascertain that the repeating nature of cache lines across snapshots (caused by transient memory changes) and their concise representation contributes most to the size reduction, accounting for 92% of the gains. Our work paves the way for further reduction in the data transferred to standby machines, thereby enhancing VM high-availability and reducing synchronization latency.

Synchronization of replicated data and program state is an essential aspect of application fault-tolerance. Current solutions use virtual memory mapping to identify page writes and replicate them at the destination. This approach has limitations because the granularity is restricted to a minimum of 4KiB per page, which may result in more data being replicated. Motivated by the emerging CXL hardware, we expand on the work Waddington, et al. [SoCC 22] by evaluating popular compression algorithms on VM snapshot data at cache line granularity. We measure the compression ratio vs. the compression time and present our conclusions.

Synchronization of replicated data and program state is an essential aspect of application fault-tolerance. Current solutions use virtual memory mapping to identify page writes and replicate them at the destination. This approach has limitations because the granularity is restricted to a minimum of 4KiB per page, which may result in more data being replicated. Motivated by the emerging CXL hardware, we expand on the work Waddington, et al. [SoCC 22] by evaluating popular compression algorithms on VM snapshot data at cache line granularity. We measure the compression ratio vs. the compression time and present our conclusions.