John E. Stone, Michael J. Hallock, James C. Phillips, Joseph R. Peterson, Zaida
Luthey-Schulten, and Klaus Schulten.
Evaluation of emerging energy-efficient heterogeneous computing
platforms for biomolecular and cellular simulation workloads.
2016 IEEE International Parallel and Distributed Processing
Symposium Workshop (IPDPSW), pp. 89-100, 2016.
(PMC: PMC4978513)
STON2016C
Many of the continuing scientific advances achieved through computational
biology are predicated on the availability of ongoing increases
in computational power required for detailed simulation
and analysis of cellular processes on biologically-relevant timescales.
A critical challenge facing the development of
future exascale supercomputer systems is the development of
new computing hardware and associated scientific applications
that dramatically improve upon the energy efficiency of existing
solutions, while providing increased simulation, analysis,
and visualization performance.
Mobile computing platforms have recently become powerful enough to support
interactive molecular visualization tasks that were previously only possible
on laptops and workstations, creating future opportunities for their convenient
use for meetings, remote collaboration, and as head mounted displays for
immersive stereoscopic viewing.
We describe early experiences adapting several biomolecular simulation
and analysis applications for emerging heterogeneous computing platforms
that combine power-efficient system-on-chip multi-core CPUs with
high-performance massively parallel GPUs. We present low-cost
power monitoring instrumentation that provides sufficient
temporal resolution to evaluate the power consumption of individual
CPU algorithms and GPU kernels. We compare the performance
and energy efficiency of scientific applications running on emerging
platforms with results obtained on traditional platforms, identify
hardware and algorithmic performance bottlenecks that affect the
usability of these platforms, and describe avenues for improving
both the hardware and applications in pursuit of the needs of
molecular modeling tasks on mobile devices and future exascale computers.
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