DAMSEL

"Parallel computational science applications have been described in terms of computation and communication patterns. An early taxonomy was the so-called seven dwarfs, later expanded to 13 (Table 1 below). Description of a parallel program in terms of patterns has continued along two primary paths, the Berkeley pattern language and the parallel patterns developed by Ralph Johnson (one of the gang of pioneering the description of design patterns). The taxonomy represented by these patterns describes the operations performed by typical simulations quite well, and petaFLOPS rates of computation have been demonstrated across a wide range of these computational motifs. However, high FLOPS rates are only part of achieving breakthrough science using computation. High I/O performance is critical from a performance and productivity perspective, to support interpretation of computational results and operation of these codes at fidelities enabled by extreme-scale computers. Codes across the range of computational motifs are finding it difficult to perform I/O on s petascale architectures, and this I/O problem may limit those ability to achieve exascale performance.

Although high-level I/O libraries have made an important contribution to supporting large parallel applications, they do not always attain a high percentage of peak performance when used from these applications. The reasons, among others, have been that (1) the underlying models, formats, and APIs in storage software did not explicitly consider parallelism in their original designs, (2) the parallelism subsequently introduced has been incremental and has often been driven to work around limitations of interfaces and underlying software (e.g., working around a specific file system performance bug), and (3) many more applications require, for scalability and algorithmic reasons, much more sophisticated data structures than what the original designs had incorporated (e.g., adaptive meshes, irregular datasets).

http://cucis.ece.northwestern.edu/projects/DAMSEL/

https://www.mcs.anl.gov/project/damsel-data-model-storage-library-exasxale-science

https://www.mcs.anl.gov/group/data-intensive-science