We provide recommendations for deployers of such systems to decide between scale up vs. scale out, as a function of their dollar or throughput constraints. Our results indicate that there is a …

Apr 18, 2025 · Before we get into the best practices, let's look at a few distributed computing concepts: horizontal scaling, vertical scaling, and linear scalability. Vertical scaling: Scale …

Feb 8, 2024 · Linear scaling means that the ratio between performance and scale are always the same when compute infrastructure stays constant. If it takes 1 second to query 1 million rows, …

Feb 8, 2025 · Fully-external graph computation systems exhibit optimal scalability by computing the ever-growing, large-scale graph with a constant amount of memory on a single machine. In …

Oct 12, 2015 · In response, a new type of framework challenges one to “think like a vertex” (TLAV) and implements user-defined programs from the perspective of a vertex rather than a …

FlashBlade is a scale-out, all-flash storage system, powered by a distributed file system purpose-built for massive concurrency across all data types. It can scale up to multi-petabyte capacity …

Algorithms that are commonly used for graph analytics have per-iteration operation counts, memory requirements, and communication costs that asymptotically scale linearly with the …

Feb 11, 2025 · In this article, we aim at achieving scalable and high-performance graph processing in PMEM. We first propose an XPLine-friendly graph storage model that uses …

To address this issue, we propose DegAwareRHH, a high performance dynamic graph data store designed for scaling out to store large, scale-free graphs by leveraging compact hash tables …

We propose Slim Graph: the first programming model and framework for practical lossy graph compression that fa-cilitates high-performance approximate graph processing, storage, and …