kerncraft/cacheprediction.py
def get_infos(self):
        """Return verbose information about the predictor."""
        first_dim_factor = self.first_dim_factor
        infos = {'memory hierarchy': [], 'cache stats': self.stats,
                 'cachelines in stats': first_dim_factor}
        for cache_level, cache_info in list(enumerate(self.machine['memory hierarchy'])):
            infos['memory hierarchy'].append({
                'index': len(infos['memory hierarchy']),
                'level': '{}'.format(cache_info['level']),
                'total loads': self.stats[cache_level]['LOAD_byte']/first_dim_factor,
                'total misses': self.stats[cache_level]['MISS_byte']/first_dim_factor,
                'total hits': self.stats[cache_level]['HIT_byte']/first_dim_factor,
                'total stores': self.stats[cache_level]['STORE_byte']/first_dim_factor,
                'total evicts': self.stats[cache_level]['EVICT_byte']/first_dim_factor,
                'total lines load': self.stats[cache_level]['LOAD_count']/first_dim_factor,
                'total lines misses': self.stats[cache_level]['MISS_count']/first_dim_factor,
                'total lines hits': self.stats[cache_level]['HIT_count']/first_dim_factor,
                'total lines stores': self.stats[cache_level]['STORE_count']/first_dim_factor,
                'total lines evicts': self.stats[cache_level]['EVICT_count']/first_dim_factor,
                'cycles': None})
        return infos
def get_infos(self):
        first_dim_factor = self.first_dim_factor
        infos = {'memory hierarchy': [], 'cache stats': self.stats,
                 'cachelines in stats': first_dim_factor}
        for cache_level, cache_info in list(enumerate(self.machine['memory hierarchy'])):
            infos['memory hierarchy'].append({
                'index': len(infos['memory hierarchy']),
                'level': '{}'.format(cache_info['level']),
                'total loads': self.stats[cache_level]['LOAD_byte']/first_dim_factor,
                'total misses': self.stats[cache_level]['MISS_byte']/first_dim_factor,
                'total hits': self.stats[cache_level]['HIT_byte']/first_dim_factor,
                'total stores': self.stats[cache_level]['STORE_byte']/first_dim_factor,
                'total evicts': self.stats[cache_level]['EVICT_byte']/first_dim_factor,
                'total lines load': self.stats[cache_level]['LOAD_count']/first_dim_factor,
                'total lines misses': self.stats[cache_level]['MISS_count']/first_dim_factor,
                'total lines hits': self.stats[cache_level]['HIT_count']/first_dim_factor,
                'total lines stores': self.stats[cache_level]['STORE_count']/first_dim_factor,
                'total lines evicts': self.stats[cache_level]['EVICT_count']/first_dim_factor,
                'cycles': None})
        return infos
def get_infos ( self ) : first_dim_factor = self . first_dim_factor infos = { 'memory hierarchy' : [ ] , 'cache stats' : self . stats , 'cachelines in stats' : first_dim_factor } for cache_level , cache_info in list ( enumerate ( self . machine [ 'memory hierarchy' ] ) ) : infos [ 'memory hierarchy' ] . append ( { 'index' : len ( infos [ 'memory hierarchy' ] ) , 'level' : '{}' . format ( cache_info [ 'level' ] ) , 'total loads' : self . stats [ cache_level ] [ 'LOAD_byte' ] / first_dim_factor , 'total misses' : self . stats [ cache_level ] [ 'MISS_byte' ] / first_dim_factor , 'total hits' : self . stats [ cache_level ] [ 'HIT_byte' ] / first_dim_factor , 'total stores' : self . stats [ cache_level ] [ 'STORE_byte' ] / first_dim_factor , 'total evicts' : self . stats [ cache_level ] [ 'EVICT_byte' ] / first_dim_factor , 'total lines load' : self . stats [ cache_level ] [ 'LOAD_count' ] / first_dim_factor , 'total lines misses' : self . stats [ cache_level ] [ 'MISS_count' ] / first_dim_factor , 'total lines hits' : self . stats [ cache_level ] [ 'HIT_count' ] / first_dim_factor , 'total lines stores' : self . stats [ cache_level ] [ 'STORE_count' ] / first_dim_factor , 'total lines evicts' : self . stats [ cache_level ] [ 'EVICT_count' ] / first_dim_factor , 'cycles' : None } ) return infos
Return verbose information about the predictor.
Return verbose information about the predictor .