Emc Corporation

Triad National Security, LLC

Ut-battelle, Inc.

Los Alamos National Security, LLC

Stephen W Poole

Gary Alan Grider

Sorin Faibish

John Michael Bent

Aaron Torres

Andrew John Dubois

Brett R Neuman

Robert W Robey

Laura Marie Morton Monroe

Decoupling loop dependencies using first in, first out (FIFO) buffers or other types of buffers to enable pipelining of loops is disclosed. By using buffers along with tailored ordering of their writes and reads, loop dependencies can be decoupled. This allows the loop to be pipelined and can lead to improved performance.

Decoupling loop dependencies using buffers to enable pipelining of loops

Parallel storage systems are provided with a burst buffer appliance for storage of a partitioned key-value store across a plurality of storage tiers. The burst buffer appliance is configured to store key-value data on first and second storage tiers comprising respective disjoint subsets of storage. One or more servers in the partitioned key-value store provide (i) an interface between one or more local key-value stores and one or more additional storage architectures, and/or (ii) a key value interface that provides access to at least one hardware key-value store. The local key-values are optionally sorted both locally by the local store and globally by the overall MDHIM framework. The local and global sorting can be leveraged to provide batch input/output (IO) operations that aggregate multiple requests into batch operations on one or more sorted ranges.

Parallel storage system with burst buffer appliance for storage of partitioned key-value store across a plurality of storage tiers

Partitioned key-value stores with one-sided communications are provided for secondary global key lookup by range-knowledgeable clients. A secondary global lookups is performed in a partitioned key-value store by receiving a request from an application for a secondary global key; accessing metadata to identify a first server storing the secondary global key; instructing the identified first server to store a first value corresponding to the requested secondary global key into a memory address of the client; and returning program control to the application, wherein the first server identifies a primary key corresponding to the requested secondary global key and instructs a second server storing the corresponding primary key to store a second value corresponding to the primary key into the memory address of the client. The second server stores the second value corresponding to the primary key into the first memory address of the client.

Partitioned key-value store with one-sided communications for secondary global key lookup by range-knowledgeable clients

Improved sorting techniques are provided that perform a parallel sort using a ranged, partitioned key-value store in a high performance computing (HPC) environment. A plurality of input data files comprising unsorted key-value data in a partitioned key-value store are sorted. The partitioned key-value store comprises a range server for each of a plurality of ranges. Each input data file has an associated reader thread. Each reader thread reads the unsorted key-value data in the corresponding input data file and performs a local sort of the unsorted key-value data to generate sorted key-value data. A plurality of sorted, ranged subsets of each of the sorted key-value data are generated based on the plurality of ranges. Each sorted, ranged subset corresponds to a given one of the ranges and is provided to one of the range servers corresponding to the range of the sorted, ranged subset. Each range server sorts the received sorted, ranged subsets and provides a sorted range. A plurality of the sorted ranges are concatenated to obtain a globally sorted result.

Parallel sort with a ranged, partitioned key-value store in a high perfomance computing environment

Collective buffering and data pattern solutions are provided for storage, retrieval, and/or analysis of data in a collective parallel processing environment. For example, a method can be provided for data storage in a collective parallel processing environment. The method comprises receiving data to be written for a plurality of collective processes within a collective parallel processing environment, extracting a data pattern for the data to be written for the plurality of collective processes, generating a representation describing the data pattern, and saving the data and the representation.

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Knoxville, TN, United States of America

Stephen W Poole