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Cache systems are widely used to speed up data retrieving. Modern HPC, data analytics, and AI/ML workloads generate vast, multi-dimensional datasets, and those data are accessed via complex queries. However, the probability of requesting the exact same data across different queries is low, leading to limited performance improvement when a traditional key-value cache is applied. In this paper, we present Mosaic-Cache, a proactive and general caching framework that enables applications with efficient partial overlapped data reuse through novel overlap-aware cache interfaces for fast content-level reuse. The core components include a metadata manager leveraging customizable indexing for fast overlap lookups, an adaptive fetch planner for dynamic cache-to-storage decisions, and an async merger to reduce cache fragmentation and redundancy. Evaluations on real-world HPC datasets show that Mosaic-Cache improves overall performance by up to 4.1× over traditional key-value-based cache while adding minimal overhead in worst-case scenarios. 

Log-Structured Merge-tree-based Key-Value Stores (LSM-KVS) are widely used to support modern, high-performance, data-intensive applications. In recent years, with the trend of deploying and optimizing LSM-KVS from monolith to Disaggregated Storage (DS) setups, the confidentiality of LSM-KVS persistent data (e.g., WAL and SST files) is vulnerable to unauthorized access from insiders and external attackers and must be protected using encryption. Existing solutions lack a high-performance design for encryption in LSM-KVS, often focus on in-memory data protection with overheads of 3.4-32.5x, and lack the scalability and flexibility considerations required in DS deployments. This paper proposes two novel designs to address the challenges of providing robust security for persistent components of LSM-KVS while maintaining high performance in both monolith and DS deployments - a simple and effective instance-level design suitable for monolithic LSM-KVS deployments, andSHIELD,a design that embeds encryption into LSM-KVS components for minimal overhead in both monolithic and DS deployment. We achieve our objective through three contributions: (1) A fine-grained integration of encryption into LSM-KVS write path to minimize performance overhead from exposure-limiting practices like using unique encryption keys per file and regularly re-encrypting using new encryption keys during compaction, (2) Mitigating performance degradation caused by recurring encryption of Write-Ahead Log (WAL) writes by using a buffering solution and (3) Extending confidentiality guarantees to DS by designing a metadata-enabled encryption-key-sharing mechanism and a secure local cache for high scalability and flexibility. We implement both designs on RocksDB, evaluating them in monolithic and DS setups while showcasing an overhead of 0-32% for the instance-level design and 0-36% for SHIELD.