ZigZag - Deep Learning Hardware Design Space Exploration
This repository presents the novel version of our tried-and-tested hardware Architecture-Mapping Design Space Exploration (DSE) Framework for Deep Learning (DL) accelerators. ZigZag bridges the gap between algorithmic DL decisions and their acceleration cost on specialized accelerators through a fast and accurate hardware cost estimation.
SalsaEngine Member List

This is the complete list of members for SalsaEngine, including all inherited members.

__init__(self, *Accelerator accelerator, LayerNode layer, SpatialMappingInternal spatial_mapping, TemporalMappingType mapping_type, **Any kwargs)SalsaEngine
acceleratorSalsaEngine
cme_queueSalsaEngine
get_prime_factors(self)SalsaEngine
get_temporal_loops(self)SalsaEngine
iteration_numberSalsaEngine
layerSalsaEngine
lpf_limitSalsaEngine
mapping_typeSalsaEngine
opt_criterion_nameSalsaEngine
run(self, Queue cme_queue)SalsaEngine
run_simulated_annealing_opt(self, cme_queue)SalsaEngine
spatial_mappingSalsaEngine
start_temperatureSalsaEngine
temporal_loop_dim_sizeSalsaEngine
temporal_mapping_lpfSalsaEngine