A performance characterization of streaming computing on supercomputers

• Streaming computing models allow for on-the-y processing of large data sets. With the increased demand for processing large amount of data in a reasonable period of time, streaming models are more and more used on supercomputers to solve data-intensive problems. Because supercomputers have been mainly used for compute-intensive workload, supercomputer performance metrics focus on the number of oating point operations in time and cannot fully characterize a streaming application performance on supercomputers. We introduce the injection and processing rates as the main metrics to characterize the performance of streaming computing on supercomputers. We analyze the dynamics of these quantities in a modi ed STREAM benchmark developed atop of an MPI streaming library in a series of di erent congurations. We show that after a brief transient the injection and processing rates converge to sustained rates. We also demonstrate that streaming computing performance strongly depends on the number of connections between data producers and consumers and on the processing task granularity.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Keyword

Big data

Data-driven applications

High-performance computing

Streaming computing

Data handling

Supercomputers

Computing performance

High performance computing

Performance characterization

Performance metrics

Processing rates

Streaming applications

Task granularity

Publication and Content Type

ref (subject category)

kon (subject category)