Michael Sevilla: Quantifying the Difference Between Scale-out and up

Monday, April 29, 2013
E2-599

Scale-up often performs better that scale-out for a small enough working set. This make sense, since many of the slow and remote components in a scale-out system (network speeds, disk speeds, etc.) can be replaced with fast and local components in a scale-up system (interprocess communication, shared memory, RAM speeds, etc.). Scale-up also offers other appealing characteristics, including a simple pro- gramming model, dynamic optimization (via the operating system), and the ability to evolve with hardware architectures.

In light of this, it is worth wondering: “Why would any business or organization choose scale-up over scale-out?” It turns out scale-out has many nice properties and a system designer would be privy to scale-out if the workload:
• has parallelism
• needs fault tolerance
• needs portability
• needs more storage
• needs more resources
• can be completed on cheaper machines

But are these properties only offered in a scale-out architecture? We show that we can achieve these properties on a scale-up system without overwhelming overheads, leading to new architectural and structural opportunities in large systems.

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