mimircache: a cache trace analysis platform

Release v0.0.2.76.

Welcome to the documentation of mimircache, a Python3 cache trace analysis platform.

The power of mimircache::
>>> import mimircache as m
>>> c = m.cachecow()
>>> c.open("trace.txt")
>>> p = c.profiler('LRU')
>>> p.get_reuse_dist()
[-1 -1 -1 -1 -1 -1 11  7 11  8  8  8 -1  8]
>>> p.plotMRC()
>>> c.heatmap('r', "hit_ratio_start_time_end_time", time_interval=10000000)
_images/example_MRC1.png _images/example_heatmap1.png

An example of MRC plot and hit ratio heatmap.

Supported Features

  • Cache replacement algorithms simulation and trace visualization.
  • A variety of cache replacement algorithms support, including LRU, LFU, MRU, FIFO, Clock, Random, ARC, SLRU, optimal and etc.
  • Hit/miss ratio curve(HRC/MRC) plotting.
  • Efficient reuse distance calculation for LRU.
  • Heatmap plotting for visulizing hit/miss ratio change over time, average reuse distance over time, etc.
  • Reuse distance distribution plotting.
  • Cache replacement algorithm comparison.


Now you can customize mimircache to fit your own need, you can

  • provide your own cache reader for reading your special cache trace files.
  • write your own profiling method for different cache replacement algorithms.
  • write a middleware for sampling your cache traces for analysis.

Indices and tables