Alan Bumgarner, Intel; Alex McDonald, NetApp; John Kim, Mellanox
Traditionally, much of the IT infrastructure that we’ve built over the years can be divided fairly simply into storage (the place we save our persistent data), network (how we get access to the storage and get at our data) and compute (memory and CPU that crunches on the data). In fact, so successful has this model been that a trip to any cloud services provider allows you to order (and be billed for) exactly these three components.
We build effective systems in a cost-optimal way by using appropriate quantities of expensive and fast memory (DRAM for instance) to cache our cheaper and slower storage. But currently fast memory has no persistence at all; it’s only storage that provides the application the guarantee that storing, modifying or deleting data does exactly that.
Memory and storage differ in other ways. For example, we load from memory to registers on the CPU, perform operations there, and then store the results back to memory by using byte addresses. This load/store technology is different from storage, where we tend to move data back and fore between memory and storage in large blocks, by using an API (application programming interface).
New memory technologies are challenging these assumptions. They look like storage in that they’re persistent, if a lot faster than traditional disks or even Flash based SSDs, but we address them in bytes, as we do memory like DRAM, if more slowly. Persistent memory (PM) lies between storage and memory in latency, bandwidth and cost, while providing memory semantics and storage persistence. In this webcast, SNIA experts will discuss:
•Traditional uses of storage and memory as a cache
•How can we build and use systems based on PM?
•What would a system with storage, persistent memory and DRAM look like?
•Do we need a new programming model to take advantage of PM?
•Interesting use cases for systems equipped with PM
•How we might take better advantage of this new technology