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.
ImcArray Member List

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

__init__(self, bool is_analog_imc, int bit_serial_precision, list[int] input_precision, int adc_resolution, int cells_size, float|None cells_area, dict[OADimension, int] dimension_sizes, bool auto_cost_extraction=False)ImcArray
__jsonrepr__(self)ImcArray
adc_resolutionImcArray
areaImcArray
area_breakdownImcArray
bit_serial_precisionImcArray
cells_w_costImcArray
energyImcArray
energy_breakdownImcArray
get_adc_cost(self)ImcArray
get_area(self)ImcArray
get_dac_cost(self)ImcArray
get_energy_for_a_layer(self, LayerNode layer, Mapping mapping)ImcArray
get_macro_level_peak_performance(self)ImcArray
get_peak_energy_single_cycle(self)ImcArray
get_tclk(self)ImcArray
mapped_rows_total_per_macroImcArray
tclkImcArray
tclk_breakdownImcArray