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2008

Tackling the Memory Balancing Problem for Large-Scale Network Simulation

10 years 4 months ago
Tackling the Memory Balancing Problem for Large-Scale Network Simulation
A key obstacle to large-scale network simulation over PC clusters is the memory balancing problem where a memory-overloaded machine can slow down an entire simulation due to disk I/O overhead. Memory balancing is complicated by (i) the difficulty of estimating the peak memory consumption of a group of nodes during network partitioning--a consequence of per-node peak memory not being synchronized--and (ii) trade-off with CPU balancing whose cost metric depends on total--as opposed to maximum--number of messages processed over time. We investigate memory balancing for large-scale network simulation which admits solutions for memory estimation and balancing not availed to small-scale or discrete-event simulation in general. First, we advance a measurement methodology for accurate and efficient memory estimation, and we establish a trade-off between memory and CPU balancing under maximum and total cost metrics. Second, we show that joint memory-CPU balancing can overcome the performance t...
Hyojeong Kim, Kihong Park
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where MASCOTS
Authors Hyojeong Kim, Kihong Park
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