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But the Google approach is not an orthodox one, as is made clear by the Google File System, the internally designed network operating system that harnesses tens of thousands of computers into a single computing system.
Many companies have made the shift from a mainframe — a single computing engine — to clusters of small server computers powered by low-cost microprocessors.
Cluster computing [3 7] is a set of stand-alone computers connected together to form a single computing resource [8, 9].
Server virtualization is an abstraction technique in which the level of computer resource utilization and flexibility are improved though the distribution of a single computing system into several resources by separating operation system from physical hardwares such as server, storage and others, and such techniques is expected to assume an important role in emission reduction [1, 2, 4].
At present, no single computing scheme satisfies both, the highly reliable operation requirement and the high-performance computing requirement.
Thus, computing centers are again looking at the price/performance benefit of sharing that single computing box via server consolidation.
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Each computing node consists of a single compute ASIC plus 256 MB of external memory.
This figure depicts high execution times of such queries on a single compute node.
This all might seem petty in the context of a single compute job, but remember that companies like IBM and Facebook are training models all day, every day for millions of customers.
In our first set of experiments, we evaluate the serial (non-parallelized) performance of our system on a single compute node.
Furthermore, modern simulations operate on data sets that are too large for all topological information to fit on a single compute node.
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