Gary Grider, HPC division leader at Los Alamos, said: “The promise of this work is to demonstrate measurably faster data query and retrieval using less energy and generating less heat. This will help speed processing during long simulations, such as tracking the very front of a shock wave traveling through a material or the state of only a few high energy particles across an extended simulation. Seagate and LANL intend to demonstrate that the potential of utilizing processing capability very near the disk devices can vastly reduce the amount of data that needs to be retrieved for the analysis part of a science campaign. “This design allows for computing to occur on erasure-encoded data which is often present in hard disk drive storage architectures.” Ed Gage, VP of the Seagate Research Group, said: “Near data computing has always relied on knowing enough about the data to act accordingly however, this architecture is the first known example of per-device computing that does not require re-constituting data into instances of the entire data set prior to exercising computing functions.

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