Ron Wilson, Altera
September 14, 2016
Two strong currents of technology change are surging across the data center, sweeping away conventional thinking and leaving behind profoundly changed software, memory, and storage architectures. One current, rising from the largely unexplored region of neural networks, is altering the way applications access data. The other, springing from the depths of semiconductor physics, is dissolving the boundary between memory and storage. Together they will fundamentally change data centers. And that change will flow straight on into embedded systems.
Infinite and Flat
Since the beginning of computing, applications have had to recognize some fundamental distinctions: between working data and files, between memory and mass storage. Even relatively recent codes like the big-data platform Hadoop studiously respect this boundary, working hard to manage DRAM and disk space for each server. But that is not really how modern programming languages view the universe.
To a Java or Python program, the world is a limitless pool of objects, all implicitly resident in main memory. Physical realities like limited DRAM, slow disk drives, and legacy interconnect schemes are issues to be made transparent, not features to be used. In place of Hadoop map/reduce, now we have Spark, with its essentially infinite pool of object-storing DRAM.
Click here to read more ...