API-cHeatmap

class PyMimircache.profiler.cHeatmap.CHeatmap(**kwargs)

heatmap class for plotting heatmaps in C

static get_breakpoints(reader, time_mode, time_interval=-1, num_of_pixel_of_time_dim=-1, **kwargs)

retrieve the breakpoints given time_mode and time_interval or num_of_pixel_of_time_dim, break point breaks the trace into chunks of given time_interval

Parameters:
  • reader – reader for reading trace
  • time_mode – either real time (r) or virtual time (v)
  • time_interval – the intended time_interval of data chunk
  • num_of_pixel_of_time_dim – the number of chunks, this is used when it is hard to estimate time_interval, you only need specify one, either num_of_pixel_of_time_dim or time_interval
  • kwargs – not used now
Returns:

a numpy list of break points begin with 0, ends with total_num_requests
heatmap(reader, time_mode, plot_type, algorithm='LRU', time_interval=-1, num_of_pixel_of_time_dim=-1, cache_params=None, **kwargs)

This functions provides different types of heatmap plotting

Parameters:
  • reader – the reader instance for data input
  • time_mode – either real time (r) or virtual time (v), real time is wall clock time, it needs the reader containing real time info virtual time is the reference number, aka. the number of requests
  • plot_type – different types of heatmap, supported heatmaps are listed in the table below
  • algorithm – cache replacement algorithm (default: LRU)
  • time_interval – the time interval of each pixel
  • num_of_pixel_of_time_dim – if don’t want to specify time_interval, you can also specify how many pixels you want
  • cache_params – params used in cache
  • kwargs – include num_of_threads, figname, enable_ihr, ema_coef(default: 0.8), info_on_fig
Returns:
plot_type required parameters descriptions
“hr_st_et” cache_size hit ratio with regarding to start time (x) and end time (y)
“hr_st_size” NOT IMPLEMENTED hit ratio with reagarding to start time (x) and size (y)
“avg_rd_st_et” NOT IMPLEMENTED average reuse distance with regaarding to start time (x) and end time (y)
“rd_distribution” N/A reuse distance distribution (y) vs time (x)
“rd_distribution_CDF” N/A reuse distance distribution CDF (y) vs time (x)
“future_rd_distribution” N/A future reuse distance distribution (y) vs time (x)
“dist_distribution” N/A absolute distance distribution (y) vs time (x)
“rt_distribution” N/A reuse time distribution (y) vs time (x)
diff_heatmap(reader, time_mode, plot_type, algorithm1, time_interval=-1, num_of_pixel_of_time_dim=-1, algorithm2='Optimal', cache_params1=None, cache_params2=None, **kwargs)
Parameters:
  • time_interval –
  • num_of_pixel_of_time_dim –
  • algorithm2 –
  • cache_params1 –
  • cache_params2 –
  • algorithm1 –
  • plot_type –
  • time_mode –
  • reader –
  • kwargs – include num_of_process, figname
Returns: