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data/data.h |
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// Copyright 2024 ETH Zurich and University of Bologna. | ||
// Licensed under the Apache License, Version 2.0, see LICENSE for details. | ||
// SPDX-License-Identifier: Apache-2.0 | ||
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{ | ||
"r": 32, | ||
"q": 32, | ||
"s": 8, | ||
"r_tiles": 2, | ||
"q_tiles": 2, | ||
"funcptr": "doitgen_baseline" | ||
} |
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#!/usr/bin/env python3 | ||
# Copyright 2024 ETH Zurich and University of Bologna. | ||
# Licensed under the Apache License, Version 2.0, see LICENSE for details. | ||
# SPDX-License-Identifier: Apache-2.0 | ||
# | ||
# Author: Luca Colagrande <[email protected]> | ||
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import numpy as np | ||
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from snitch.util.sim import data_utils | ||
from snitch.util.sim.data_utils import format_array_definition, format_struct_definition, DataGen | ||
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np.random.seed(42) | ||
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DOUBLE_BUFFER = True | ||
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class DoitgenDataGen(DataGen): | ||
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# Function pointers to alternative implementations | ||
FUNCPTRS = ["doitgen_naive", "doitgen_baseline", "doitgen_opt"] | ||
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def golden_model(self, A, x): | ||
R, Q, S = A.shape | ||
P, _ = x.shape | ||
Aout = np.ndarray((R, Q, P)) | ||
for r in range(R): | ||
for q in range(Q): | ||
for p in range(P): | ||
Aout[r, q, p] = 0 | ||
for s in range(S): | ||
Aout[r, q, p] += A[r, q, s] * x[p, s] | ||
return Aout | ||
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def validate(self, **kwargs): | ||
n_cores = 8 | ||
assert (kwargs['r'] % kwargs['r_tiles']) == 0, "r must be an integer multiple of r_tiles" | ||
assert (kwargs['q'] % kwargs['q_tiles']) == 0, "q must be an integer multiple of q_tiles" | ||
if kwargs['funcptr'] != 'doitgen_naive': | ||
assert (kwargs['s'] % 4) == 0, "s must be an integer multiple of unrolling factor" | ||
r_per_tile = kwargs['r'] / kwargs['r_tiles'] | ||
q_per_tile = kwargs['q'] / kwargs['q_tiles'] | ||
assert (r_per_tile % n_cores) == 0, "r_per_tile must be an integer multiple of n_cores" | ||
assert kwargs['funcptr'] in self.FUNCPTRS, f"Function pointer must be among {self.FUNCPTRS}" | ||
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# Calculate total TCDM occupation | ||
a_tile_size = r_per_tile * q_per_tile * kwargs['s'] * 8 | ||
x_size = kwargs['s'] * kwargs['s'] * 8 | ||
total_size = 2 * a_tile_size + x_size | ||
if DOUBLE_BUFFER: | ||
total_size *= 2 | ||
data_utils.validate_tcdm_footprint(total_size) | ||
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def emit_header(self, **kwargs): | ||
header = [super().emit_header()] | ||
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self.validate(**kwargs) | ||
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A = np.random.randint(-100, 100, size=(kwargs['r'], kwargs['q'], kwargs['s'])) | ||
x = np.random.randint(-100, 100, size=(kwargs['s'], kwargs['s'])) | ||
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_ = self.golden_model(A, x) | ||
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A = A.flatten() | ||
x = x.flatten() | ||
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A_uid = 'A' | ||
x_uid = 'x' | ||
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cfg = { | ||
'r': kwargs['r'], | ||
'q': kwargs['q'], | ||
's': kwargs['s'], | ||
'A': A_uid, | ||
'x': x_uid, | ||
'r_tiles': kwargs['r_tiles'], | ||
'q_tiles': kwargs['q_tiles'], | ||
'funcptr': kwargs['funcptr'] | ||
} | ||
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header += [format_array_definition('double', A_uid, A)] | ||
header += [format_array_definition('double', x_uid, x)] | ||
header += [format_struct_definition('doitgen_args_t', 'args', cfg)] | ||
header = '\n\n'.join(header) | ||
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return header | ||
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if __name__ == '__main__': | ||
DoitgenDataGen().main() |
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#!/usr/bin/env python3 | ||
# Copyright 2024 ETH Zurich and University of Bologna. | ||
# Licensed under the Apache License, Version 2.0, see LICENSE for details. | ||
# SPDX-License-Identifier: Apache-2.0 | ||
# | ||
# Luca Colagrande <[email protected]> | ||
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import numpy as np | ||
import sys | ||
from datagen import DoitgenDataGen | ||
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from snitch.util.sim.verif_utils import Verifier | ||
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class DoitgenVerifier(Verifier): | ||
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OUTPUT_UIDS = ['A'] | ||
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def __init__(self): | ||
super().__init__() | ||
self.func_args = { | ||
'r': 'I', | ||
'q': 'I', | ||
's': 'I', | ||
'A': 'I', | ||
'x': 'I', | ||
'r_tiles': 'I', | ||
'q_tiles': 'I', | ||
'funcptr': 'I' | ||
} | ||
self.func_args = self.get_input_from_symbol('args', self.func_args) | ||
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def get_actual_results(self): | ||
return self.get_output_from_symbol(self.OUTPUT_UIDS[0], 'double') | ||
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def get_expected_results(self): | ||
A = self.get_input_from_symbol('A', 'double') | ||
A = np.reshape(A, (self.func_args['r'], self.func_args['q'], self.func_args['s'])) | ||
x = self.get_input_from_symbol('x', 'double') | ||
x = np.reshape(x, (self.func_args['s'], self.func_args['s'])) | ||
return DoitgenDataGen().golden_model(A, x).flatten() | ||
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def check_results(self, *args): | ||
return super().check_results(*args, rtol=1e-10) | ||
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if __name__ == "__main__": | ||
sys.exit(DoitgenVerifier().main()) |
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// Copyright 2024 ETH Zurich and University of Bologna. | ||
// Licensed under the Apache License, Version 2.0, see LICENSE for details. | ||
// SPDX-License-Identifier: Apache-2.0 | ||
// | ||
// Author: Luca Colagrande <[email protected]> | ||
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#pragma once | ||
#include <stdint.h> | ||
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typedef void (*doitgen_fp_t)(uint32_t r, uint32_t q, uint32_t s, double *A, | ||
double *x, double *Aout); | ||
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typedef struct { | ||
uint32_t r; | ||
uint32_t q; | ||
uint32_t s; | ||
double *A; | ||
double *x; | ||
uint32_t r_tiles; | ||
uint32_t q_tiles; | ||
doitgen_fp_t funcptr; | ||
} doitgen_args_t; |
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