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Computational storage series: Prizsm - Data disaggregation & likable latency

Computational storage: What is it? Why now, what for, who from? Customer experience market made leap forward during pandemic Download Current Issue Software runs on data and data is often regarded as the new oil. So it makes sense to put data as close to where it is being processed as possible, in order to reduce latency for performance-hungry processing tasks. Some architectures call for big chunks of memory-like storage located near the compute function, while, conversely, in some cases, it makes more sense to move the compute nearer to the bulk storage. In this series of articles we explore the architectural decisions driving modern data processing… and, specifically, we look at computational storage

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Computational storage series: Evaluator Group - Speculations, expectations & extrapolations

Five ways to boost systems utilisation in the datacentre Interview: ONS data science chief Tom Smith on government data capability Download Current Issue Software runs on data and data is often regarded as the new oil. So it makes sense to put data as close to where it is being processed as possible, in order to reduce latency for performance-hungry processing tasks. Some architectures call for big chunks of memory-like storage located near the compute function, while, conversely, in some cases, it makes more sense to move the compute nearer to the bulk storage. In this series of articles we explore the architectural decisions driving modern data processing… and, specifically, we look at computational storage

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Computational storage series: Model9 - The cloud + computational storage sweet spot

Computational storage series: Model9 - The cloud + computational storage sweet spot
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Computational storage: What is it? Why now, what for, who from?

Computational storage: What is it? Why now, what for, who from? Computational storage is an emerging architecture category, in which compute is put near storage to address I/O bottlenecks resulting from large volumes of data Share this item with your network: By Published: 11 May 2021 Handling data at the network edge is not a new idea, but it is becoming more important as organisations grapple with growing data volumes and the need to process information quickly. Computational storage is, however, a relatively new way to tackle that challenge. A key driver here is that conventional IT systems, with separate compute, networking and storage components, come with inherent bottlenecks.

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Computational storage: A Computer Weekly analysis series

CW Developer Network Latest Blog Posts Related Content CIO interview: Richard Corbridge, Boots Starting a career in the digital economy Download Current Issue Software runs on data and data is often regarded as the new oil. So it makes sense to put data as close to where it is being processed as possible, in order to reduce latency for performance-hungry processing tasks. Some architectures call for big chunks of memory-like storage located near the compute function, while, conversely, in some cases, it makes more sense to move the compute nearer to the bulk storage. In this series of articles we explore the architectural decisions driving modern data processing.

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