def get_presolved_bounds(self) -> Union[Tuple[List[float]], None]:
if not self.run_successful:
raise Exception(
"Papilo run failed, cannot retriece solved bounds!")
out = OutputGrabber()
with out:
reader: FileReaderInterface = get_reader(self.output_file)
return reader.get_var_bounds()
def propagation_measure_run(input_file: str):
print("\n========== Starting measure executions for the ", input_file,
" file. ==========\n")
out = OutputGrabber(sys.stderr)
# with out:
reader: FileReaderInterface = get_reader(input_file)
n_cons = reader.get_n_cons()
n_vars = reader.get_n_vars()
nnz = reader.get_nnz()
lbs, ubs = reader.get_var_bounds()
lhss, rhss = reader.get_lrhss()
coeffs, row_ptrs, col_indices = reader.get_cons_matrix()
vartypes = reader.get_SCIP_vartypes()
lbs = list(filter(lambda x: x < -1e20, lbs))
ubs = list(filter(lambda x: x > 1e20, ubs))
print("num inf: ", len(lbs) + len(ubs))
exit(1)
# print sparsity and input data size
print("num vars: ", n_vars)
print("num cons: ", n_cons)
print("nnz : ", nnz)
lbs_seq = lbs_gpuatomic = lbs
ubs_seq = ubs_gpuatomic = ubs
(seq_new_lbs, seq_new_ubs) = propagateSequentialWithMeasure(
n_vars, n_cons, nnz, col_indices, row_ptrs, coeffs, lhss, rhss,
lbs_seq, ubs_seq, vartypes)
(gpuatomic_new_lbs, gpuatomic_new_ubs) = propagateGPUAtomicWithMeasure(
n_vars, n_cons, nnz, col_indices, row_ptrs, coeffs, lhss, rhss,
lbs_gpuatomic, ubs_gpuatomic, vartypes)
seq_new_lbs = normalize_infs(seq_new_lbs)
seq_new_ubs = normalize_infs(seq_new_ubs)
gpuatomic_new_lbs = normalize_infs(gpuatomic_new_lbs)
gpuatomic_new_ubs = normalize_infs(gpuatomic_new_ubs)
equal_seq_gpu_atomic = arrays_equal(seq_new_lbs,
gpuatomic_new_lbs) and arrays_equal(
seq_new_ubs, gpuatomic_new_ubs)
print("cpu_seq to gpu_atomic results match: ", equal_seq_gpu_atomic)
print(out.capturedtext)
print("========== End measure executions for the ", input_file,
" file. ==========\n")
def propagation_measure_run(input_file: str):
out = OutputGrabber()
with out:
reader: FileReaderInterface = get_reader(input_file)
n_cons = reader.get_n_cons()
n_vars = reader.get_n_vars()
nnz = reader.get_nnz()
lbs, ubs = reader.get_var_bounds()
lhss, rhss = reader.get_lrhss()
coeffs, row_ptrs, col_indices = reader.get_cons_matrix()
vartypes = reader.get_SCIP_vartypes()
# print sparsity and input data size
print("num vars: ", n_vars)
print("num cons: ", n_cons)
print("nnz : ", nnz)
lbs_seq = lbs_gpuatomic = lbs
ubs_seq = ubs_gpuatomic = ubs
(seq_new_lbs, seq_new_ubs) = propagateSequentialWithMeasure(
n_vars, n_cons, nnz, col_indices, row_ptrs, coeffs, lhss, rhss,
lbs_seq, ubs_seq, vartypes)
(gpuatomic_new_lbs, gpuatomic_new_ubs) = propagateGPUAtomicWithMeasure(
n_vars, n_cons, nnz, col_indices, row_ptrs, coeffs, lhss, rhss,
lbs_gpuatomic, ubs_gpuatomic, vartypes)
seq_new_lbs = normalize_infs(seq_new_lbs)
seq_new_ubs = normalize_infs(seq_new_ubs)
gpuatomic_new_lbs = normalize_infs(gpuatomic_new_lbs)
gpuatomic_new_ubs = normalize_infs(gpuatomic_new_ubs)
equal_seq_gpu_atomic = arrays_equal(
seq_new_lbs, gpuatomic_new_lbs) and arrays_equal(
seq_new_ubs, gpuatomic_new_ubs)
print("cpu_seq to gpu_atomic results match: ", equal_seq_gpu_atomic)
print(out.capturedtext)
plot_progress_save_pdf(out.capturedtext)
def prop_compare_seq_gpu(lp_file_path: str,
datatype: _SimpleCData = c_double,
seed: int = 0,
synctype: int = 0) -> None:
reader: FileReaderInterface = get_reader(lp_file_path)
n_cons = reader.get_n_cons()
n_vars = reader.get_n_vars()
nnz = reader.get_nnz()
lbs, ubs = reader.get_var_bounds()
lhss, rhss = reader.get_lrhss()
coeffs, row_ptrs, col_indices = reader.get_cons_matrix()
vartypes = reader.get_SCIP_vartypes()
#num_seeds = 5
# for seed in range(num_seeds):
# print("\nRunning seed ", seed)
if seed != 0:
coeffs, col_indices, row_ptrs, lbs, ubs, lhss, rhss, vartypes = permute_mip(
n_cons, n_vars, coeffs, col_indices, row_ptrs, lbs, ubs, lhss,
rhss, vartypes, seed)
exec_run(n_vars, n_cons, nnz, coeffs, col_indices, row_ptrs, lbs, ubs,
lhss, rhss, vartypes, synctype)
def papilo_comparison_run(lp_file_path: str,
papilo_path: str,
datatype: _SimpleCData = c_double) -> None:
reader: FileReaderInterface = get_reader(lp_file_path)
n_cons = reader.get_n_cons()
n_vars = reader.get_n_vars()
nnz = reader.get_nnz()
lbs, ubs = reader.get_var_bounds()
lhss, rhss = reader.get_lrhss()
coeffs, row_ptrs, col_indices = reader.get_cons_matrix()
vartypes = reader.get_SCIP_vartypes()
# print sparsity and input data size
print("num vars: ", n_vars)
print("num cons: ", n_cons)
print("nnz : ", nnz)
lbs_dis = lbs_seq = lbs_gpuatomic = lbs_gpu = lbs_omp = lbs
ubs_dis = ubs_seq = ubs_gpuatomic = ubs_gpu = ubs_omp = ubs
with OutputGrabber():
(tmp_lbs, tmp_ubs) = propagateSequential(n_vars,
n_cons,
nnz,
col_indices,
row_ptrs,
coeffs,
lhss,
rhss,
lbs_dis,
ubs_dis,
vartypes,
datatype=datatype)
tmp_lbs = normalize_infs(tmp_lbs)
tmp_ubs = normalize_infs(tmp_ubs)
# (omp_new_lbs, omp_new_ubs) = propagateFullOMP(n_vars, n_cons, nnz, col_indices, row_ptrs, coeffs, lhss, rhss, lbs_omp, ubs_omp, vartypes, datatype=c_double)
(seq_new_lbs, seq_new_ubs,
stdout) = propagateSequentialWithPapiloPostsolve(reader,
n_vars,
n_cons,
nnz,
col_indices,
row_ptrs,
coeffs,
lhss,
rhss,
lbs_seq,
ubs_seq,
vartypes,
papilo_path,
datatype=c_double)
print("papilo execution start...")
papilo = PapiloInterface(lp_file_path, papilo_path)
papilo_output = papilo.run_papilo(use_rationals=False)
lbs_papilo, ubs_papilo = papilo.get_presolved_bounds()
print("papilo propagation done. Num rounds: ", papilo.get_num_rounds())
print("papilo execution time : ", papilo.get_exec_time(), " seconds")
#print("papilo outputL \n", papilo_output)
# omp_new_lbs = normalize_infs(omp_new_lbs)
# omp_new_ubs = normalize_infs(omp_new_ubs)
seq_new_lbs = normalize_infs(seq_new_lbs)
seq_new_ubs = normalize_infs(seq_new_ubs)
lbs_papilo = normalize_infs(lbs_papilo)
ubs_papilo = normalize_infs(ubs_papilo)
# equal_seq_omp = arrays_equal(tmp_lbs, omp_new_lbs) and arrays_equal(tmp_ubs, omp_new_ubs)
equal_seq_papilo = arrays_equal(seq_new_lbs, lbs_papilo) and arrays_equal(
seq_new_ubs, ubs_papilo)
# print("cpu_seq to cpu_omp results match: ", equal_seq_omp)
print("cpu_seq to pailo results match: ", equal_seq_papilo)
print("all results match: ", equal_seq_papilo)
def prop_compare_seq_gpu(lp_file_path: str,
datatype: _SimpleCData = c_double) -> None:
reader: FileReaderInterface = get_reader(lp_file_path)
n_cons = reader.get_n_cons()
n_vars = reader.get_n_vars()
nnz = reader.get_nnz()
lbs, ubs = reader.get_var_bounds()
lhss, rhss = reader.get_lrhss()
coeffs, row_ptrs, col_indices = reader.get_cons_matrix()
vartypes = reader.get_SCIP_vartypes()
# print sparsity and input data size
print("num vars: ", n_vars)
print("num cons: ", n_cons)
print("nnz : ", nnz)
lbs_dis = lbs_seq = lbs_gpuatomic = lbs_gpu = lbs_omp = lbs
ubs_dis = ubs_seq = ubs_gpuatomic = ubs_gpu = ubs_omp = ubs
(seq_new_lbs, seq_new_ubs) = propagateSequential(n_vars,
n_cons,
nnz,
col_indices,
row_ptrs,
coeffs,
lhss,
rhss,
lbs_seq,
ubs_seq,
vartypes,
datatype=c_double)
(omp_new_lbs, omp_new_ubs) = propagateFullOMP(n_vars,
n_cons,
nnz,
col_indices,
row_ptrs,
coeffs,
lhss,
rhss,
lbs_omp,
ubs_omp,
vartypes,
datatype=c_double)
# (gpu_new_lbs, gpu_new_ubs) = propagateGPUReduction(n_vars, n_cons, nnz, col_indices, row_ptrs, coeffs, lhss, rhss, lbs_gpu, ubs_gpu, vartypes, datatype=datatype)
# (dis_new_lbs, dis_new_ubs) = propagateSequentialDisjoint( n_vars, n_cons, nnz, col_indices, row_ptrs, coeffs, lhss, rhss, lbs_dis, ubs_dis, vartypes)
# idx = 1
(gpuatomic_new_lbs,
gpuatomic_new_ubs) = propagateGPUAtomic(n_vars,
n_cons,
nnz,
col_indices,
row_ptrs,
coeffs,
lhss,
rhss,
lbs_gpuatomic,
ubs_gpuatomic,
vartypes,
fullAsync=False,
datatype=datatype)
seq_new_lbs = normalize_infs(seq_new_lbs)
seq_new_ubs = normalize_infs(seq_new_ubs)
# gpu_new_lbs = normalize_infs(gpu_new_lbs)
# gpu_new_ubs = normalize_infs(gpu_new_ubs)
omp_new_lbs = normalize_infs(omp_new_lbs)
omp_new_ubs = normalize_infs(omp_new_ubs)
gpuatomic_new_lbs = normalize_infs(gpuatomic_new_lbs)
gpuatomic_new_ubs = normalize_infs(gpuatomic_new_ubs)
# # dis_new_lbs = normalize_infs(dis_new_lbs)
# # dis_new_ubs = normalize_infs(dis_new_ubs)
#
equal_seq_omp = arrays_equal(seq_new_lbs, omp_new_lbs) and arrays_equal(
seq_new_ubs, omp_new_ubs)
equal_seq_gpu_atomic = arrays_equal(seq_new_lbs,
gpuatomic_new_lbs) and arrays_equal(
seq_new_ubs, gpuatomic_new_ubs)
# equal_seq_gpu_full = arrays_equal(seq_new_lbs, gpu_new_lbs) and arrays_equal(seq_new_ubs, gpu_new_ubs)
# # equal_seq_dis = arrays_equal(seq_new_lbs, dis_new_lbs) and arrays_equal(seq_new_ubs, dis_new_ubs)
print("\ncpu_seq to cpu_omp results match: ", equal_seq_omp)
# print("cpu_seq to gpu_reduction results match: ", equal_seq_gpu_full)
print("cpu_seq to gpu_atomic results match: ", equal_seq_gpu_atomic)
# # print("cpu_seq to cpu_seq_dis results match: ", equal_seq_dis)
print("all results match: ", equal_seq_gpu_atomic and equal_seq_omp)