I have to disagree. PHold was not designed to run well under Time Warp. It was designed as a stress test for any parallel discrete event simulator, whether based on Time Warp or not, and in particular originally to compare optimistic to conservative synchronization algorithms. Also, Sequoia is much less biased toward regular geometry continuum simulations that other world class supercomputers. It has no GPUs, for example. Machines of this class will be used more and more in the future for discrete simulations such as network models, or agent-based models, or for huge data problems, or for mixed continuous-discrete models such as of the power grid.
The simulation was a well-known parallel discrete event benchmark called PHold. It is not a model of any particular physical system, but is more of a stress and scalability test for the simulator, in this case the ROSS simulator developed at RPI. PHold has particularly fine-grained events, which stresses the synchronization mechanism known as Time Warp, implemented ROSS with support for reverse computation. It stresses the scalability of the Global Virtual Time commitment mechanism (used for I/O, error detection, storage management, and termination detection). And because PHold has no locality in its communication, it greatly stresses the underlying communication layer, MPI. The general idea is that a simulator that can achieve high performance on PHold at very large parallel scale can achieve high performance on just about any realistic, load balanced discrete event simulation at that scale.
I would think that the macroscopic behavior of 3.5 million atoms in (poly)crystals or in a fluid or plasma states are within the capability of Sequoia. That's about 2 atoms per core and per GB of RAM. But the complex dynamics of proteins, DNA, RNA, and any other complex polymers that comprise the polio virus interacting with, say, a cell membrane, are still probably out of reach for accurate calculation in a reasonable amount of time.
It runs a custom IBM OS specifically designed for Blue Gene/Q. It proveds an API very similar to Linux, but with some restrictions, e.g. static limits on threads, no process forking, and custom MPI messaging instead of a TCP/IP stack.
The title to this piece is wrong. The supercomputer in question was Sequoia, the Blue Gene/Q supercomputer located at Lawrence Livermore National Laboratory. Some preliminary work was done on a smaller RPI BG/Q machine, however. (I am a coauthor of the paper.)
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I have to disagree. PHold was not designed to run well under Time Warp. It was designed as a stress test for any parallel discrete event simulator, whether based on Time Warp or not, and in particular originally to compare optimistic to conservative synchronization algorithms. Also, Sequoia is much less biased toward regular geometry continuum simulations that other world class supercomputers. It has no GPUs, for example. Machines of this class will be used more and more in the future for discrete simulations such as network models, or agent-based models, or for huge data problems, or for mixed continuous-discrete models such as of the power grid.
The simulation was a well-known parallel discrete event benchmark called PHold. It is not a model of any particular physical system, but is more of a stress and scalability test for the simulator, in this case the ROSS simulator developed at RPI. PHold has particularly fine-grained events, which stresses the synchronization mechanism known as Time Warp, implemented ROSS with support for reverse computation. It stresses the scalability of the Global Virtual Time commitment mechanism (used for I/O, error detection, storage management, and termination detection). And because PHold has no locality in its communication, it greatly stresses the underlying communication layer, MPI. The general idea is that a simulator that can achieve high performance on PHold at very large parallel scale can achieve high performance on just about any realistic, load balanced discrete event simulation at that scale.
I would think that the macroscopic behavior of 3.5 million atoms in (poly)crystals or in a fluid or plasma states are within the capability of Sequoia. That's about 2 atoms per core and per GB of RAM. But the complex dynamics of proteins, DNA, RNA, and any other complex polymers that comprise the polio virus interacting with, say, a cell membrane, are still probably out of reach for accurate calculation in a reasonable amount of time.
It runs a custom IBM OS specifically designed for Blue Gene/Q. It proveds an API very similar to Linux, but with some restrictions, e.g. static limits on threads, no process forking, and custom MPI messaging instead of a TCP/IP stack.
The title to this piece is wrong. The supercomputer in question was Sequoia, the Blue Gene/Q supercomputer located at Lawrence Livermore National Laboratory. Some preliminary work was done on a smaller RPI BG/Q machine, however. (I am a coauthor of the paper.)