Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
Predicting Memcache Throughput using Simulation and Modeling
IEEE Symposium on Theory of Modeling and Simulation (TMS)
Abstract
The current work introduces a method for predicting Memcached throughput on single-core and multi-core processors. The method is based on traces collected from a full system simulator running Memcached.
A series of microarchtectural simulators consume these traces and the results are used to produce a CPI model composed of a baseline issue rate, cache miss rates, and branch mispredictions rate.
Simple queueing models are used to produce throughput predictions with accuracy in the range of 8% to 17%.
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