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Pure Storage Announces Breakthrough STAC-M3 Benchmark Testing Results for High-performance and Quantitative Trading

Pure Storage

Pure Storage Announces Breakthrough STAC-M3 Benchmark Testing Results for High-performance and Quantitative Trading by Pure Storage Blog In the fast-paced world of high-frequency and quantitative trading , every microsecond counts. 17 of 24 STAC-M3 Kanaga mean-response time benchmarks exhibited enhancements, such as a 1.3x-1.5x

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MPI Storage Benchmarks with Docker

Pure Storage

Two common benchmarks used in HPC environments are IOR and mdtest , focusing on throughput and filesystem metadata respectively. These benchmarks are based on MPI for multi-computer processing. Predictable management of library dependencies and software versions. Application isolation in a set of shared physical resources.

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Digital Twins and the Future of Physical Security and Risk Management

Security Industry Association

The result: Facilities are managing expensive, inefficient and wasteful physical security protocols. Today’s technology advances, such as cloud computing, deep learning and IoT, enable the application of enterprise data to mitigate risks and accurately and efficiently manage facilities’ security systems.

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Docker vs. Podman

Pure Storage

Unlike Docker’s client-server architecture with a background daemon, Podman takes a more lightweight and security-focused approach that leverages existing container technologies like libpod and runc. What Is Podman? Developed by Red Hat, Podman is an alternative to Docker that offers similar containerization capabilities.

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Docker vs. Podman

Pure Storage

Unlike Docker’s client-server architecture with a background daemon, Podman takes a more lightweight and security-focused approach that leverages existing container technologies like libpod and runc. What Is Podman? Developed by Red Hat, Podman is an alternative to Docker that offers similar containerization capabilities.

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7 Habits of Successful Generative AI Adopters by Dormain Drewitz

PagerDuty

After talking to data scientists, data engineers, and product managers working on AI-generated features, a few patterns have emerged. She credits a strong data architecture foundation as critical to moving quickly with generative AI. Yet, slow and onerous architectural reviews can kill innovation.

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SQreamDB on FlashBlade//S

Pure Storage

The workload chosen was TPCx-BB , aka “Big Bench,” due to the broad industry applicability, access to the data generation tool, and the ability to compare against pre-existing benchmarks run by SQream on other platforms. The full TPCx-BB benchmark will not be tested as the environment is not set up to do so.