Storage devices and servers are getting ever faster and larger, but I/O links and networks are not keeping up at the same pace, leading to bottlenecks in storage and computation stacks. Computational storage, a form of near data processing, moves a variety of functions closer to the edge where data is physically stored. This allows parallel computation, which reduces I/O traffic and eases other constraints on existing compute, memory, storage, and I/O. This session will introduce how Intel Labs scientists used a block-compatible design based on virtual objects, making numerous offloads possible in block-based computational storage. This method reduces the network load and improves speed, opening up additional resources and flexibility in how computations are distributed throughout the entire system.
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