Abstract
Scientific applications are diverse in terms of the resource
requirements, and tend to vary significantly from commercial
applications. In order to provide sustained performance, a target high
performance computing (HPC) platform must offer a balance between CPU
performance to memory, interconnect and I/O subsystems performance. We
characterize the system balance requirements for two large-scale
Office of Science applications, GYRO (fusion simulation) and POP
(climate modeling), and develop platform-independent parameterized
requirement models. We measure the parallel efficiencies for GYRO and
POP on three multiprocessor systems: an SMP cluster (IBM p690), a
shared-memory system (SGI Altix) and a vector supercomputer (Cray X1). The
higher computational intensity and interconnect bandwidth requirements
of GYRO result in higher performance efficiencies on the vector
platform. At the same time, small message sizes in POP benefit from
low MPI latencies of the shared-memory platform. Overall results confirm
system balance requirements that are generated by the requirement
models.
