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Scaling Software Builds in Azure with FlashBlade in a Cloud-Adjacent Architecture

Pure Storage

Pure Storage ® , Azure, and Equinix have collaborated to develop a connected-cloud architecture for EDA and highly parallel HPC workloads, such as software build and testing. There are many advantages to this particular architecture. We conducted a performance test of this architecture. Parallel Build Experiment.

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Scaling Software Builds in Azure with FlashBlade in a Cloud-Adjacent Architecture

Pure Storage

Pure Storage ® , Azure, and Equinix have collaborated to develop a connected-cloud architecture for EDA and highly parallel HPC workloads, such as software build and testing. There are many advantages to this particular architecture. We conducted a performance test of this architecture. Parallel Build Experiment.

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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. Its daemonless architecture translates to lower resource consumption, making it suitable for resource-constrained environments.

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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. Its daemonless architecture translates to lower resource consumption, making it suitable for resource-constrained environments.

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TPUs vs. GPUs: What’s the Difference?

Pure Storage

GPUs are generally faster than CPUs for deep learning tasks, but the specialized architecture of TPUs often allows them to be faster than GPUs. Benchmarks comparing TPUs and GPUs in machine learning tasks have shown that TPUs often outperform GPUs in terms of training speed and efficiency.

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TPUs vs. GPUs: What’s the Difference?

Pure Storage

GPUs are generally faster than CPUs for deep learning tasks, but the specialized architecture of TPUs often allows them to be faster than GPUs. Benchmarks comparing TPUs and GPUs in machine learning tasks have shown that TPUs often outperform GPUs in terms of training speed and efficiency.

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7 Habits of Successful Generative AI Adopters by Dormain Drewitz

PagerDuty

She credits a strong data architecture foundation as critical to moving quickly with generative AI. Yet, slow and onerous architectural reviews can kill innovation. How did Goswami and team strike a balance to move quickly, but not paint the architecture into a corner?