Abstract
Modern supercomputers host numerous jobs that compete for shared storage resources, causing I/O interference and performance degradation. Solutions based on software- defined storage (SDS) emerged to address this issue by coordinating the storage environment through the enforcement of QoS policies. However, these often fail to consider the scale of modern HPC infrastructures.In this work, we explore the advantages and shortcomings of state-of-the-art SDS solutions and highlight the scale of current production clusters and their rising trends. Furthermore, we conduct the first experimental study that sheds new insights into the performance and scalability of flat and hierarchical SDS control plane designs.Our results, using the Frontera supercomputer, show that a flat design with a single controller can scale up to 2,500 nodes with an average control cycle latency of 41 ms, while hierarchical designs can handle up to 10,000 nodes with an average latency ranging between 69 and 103 ms. © 2024 IEEE.

Abstract
There are now multiple proposals for Conflict-free Replicated Data Types (CRDTs) in SQL databases aimed at distributed systems. Some, such as ElectricSQL, provide only relational tables as convergent replicated maps, but this omits semantics that would be useful for merging updates. Others, such as Pg\_crdt, provide access to a rich library of encapsulated column types. However, this puts merge and query processing outside the scope of the query optimizer and restricts the ability of an administrator to influence access paths with materialization and indexes. Our proposal, CRDV, overcomes this challenge by using two layers implemented as SQL views: The first provides a replicated relational table from an update history, while the second implements varied and rich types on top of the replicated table. This allows the definition of merge semantics, or even entire new data types, in SQL itself, and enables global optimization of user queries together with merge operations. Therefore, it naturally extends the scope of query optimization and local transactions to operations on replicated data, can be used to reproduce the functionality of common CRDTs with simple SQL idioms, and results in better performance than alternatives.

Abstract
Developers of data-intensive georeplicated applications face a difficult decision when selecting a database system. As captured by the CAP theorem, CP systems such as Spanner provide strong consistency that greatly simplifies application development. AP systems such as AntidoteDB providing Transactional Causal Consistency (TCC), ensure availability in face of network partitions and isolate performance from wide-area round-trip times, but avoid lost-update anomalies only when values can be merged. Ideally, an application should be able to adapt to current data and network conditions by selecting which transactional consistency to use for each transaction. In this paper, we test the hypothesis that a georeplicated database system can be built at its core providing only TCC, hence, being AP, but allow an application to execute some transactions under Snapshot Isolation (SI), hence CP. Our main result is showing that this can be achieved even when all the interaction happens through the TCC database system, without additional communication channels between the participants. A preliminary experimental evaluation with a proof-of-concept implementation using AntidoteDB shows that this approach is feasible. Copyright © 2025 held by the owner/author(s).