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Large-scale science instruments, such as the distributed radio telescopeLOFAR, show that we are in an era of data-intensive scientific discovery. Suchinstruments rely critically on significant computing resources, both hardwareand software, to do science. Considering limited science budgets, and the smallfraction of these that can be dedicated to compute hardware and software, thereis a strong and obvious desire for low-cost computing. However, optimising forcost is only part of the equation; the value potential over the lifetime of thesolution should also be taken into account. Using a tangible example, computehardware, we introduce a conceptual model to approximate the lifetime relativescience value of such a system. While the introduced model is not intended toresult in a numeric value for merit, it does enumerate some components thatdefine this metric. The intent of this paper is to show how compute systemrelated design and procurement decisions in data-intensive science projectsshould be weighed and valued. By using both total cost and science value as adriver, the science output per invested Euro is maximised. With a number ofcase studies, focused on computing applications in radio astronomy past,present and future, we show that the hardware-based analysis can be, and hasbeen, applied more broadly.

On optimising cost and value in compute systems for radio astronomy