完善脚本功能,添加计时估计
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@@ -31,13 +31,13 @@ else:
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tree = None
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tree = comm.bcast(tree, root=0)
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arrays = [torch.from_numpy(np.ascontiguousarray(t._data, dtype=np.complex128)) for t in tn.tensors]
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arrays = [torch.from_numpy(np.asarray(t._data)) for t in tn.tensors]
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n_slices = tree.multiplicity
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if rank == 0:
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print(f"Slices: {n_slices}, Ranks: {size}, "
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f"Peak: {tree.max_size() * 16 / 1e9:.2f} GB, "
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f"Threads/rank: {max(1, NCORES // size)}, Backend: torch")
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f"Threads/rank: {NCORES}, Backend: torch")
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t0 = time.time()
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result = None
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@@ -8,7 +8,7 @@ with open(f"data/tree_q{NQUBITS}_l{NLAYERS}.pkl", 'rb') as f:
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print(f"Original peak: {tree.max_size() * 16 / 1e9:.2f} GB")
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tree_sliced = tree.slice_and_reconfigure(target_size=2**30) # 2^29 = 8 GB
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tree_sliced = tree.slice_and_reconfigure(target_size=2**28)
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with open(f"data/tree_q{NQUBITS}_l{NLAYERS}_sliced.pkl", 'wb') as f:
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pickle.dump(tree_sliced, f)
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@@ -5,9 +5,21 @@ path = sys.argv[1] if len(sys.argv) > 1 else "data/tree_q25_l10.pkl"
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with open(path, 'rb') as f:
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tree = pickle.load(f)
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# Intel 8558P: 96 cores, 2.1GHz, AVX-512 (16 FP64/cycle), FMA x2
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# complex128 multiply-add = 6 real FLOPs
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CORES = 96
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FREQ = 2.1e9
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AVX512_FP64 = 16
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TFLOPS = CORES * FREQ * AVX512_FP64 * 2 / 1e12 # ~6.45 TFLOPS real FP64
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COMPLEX_FLOPS = TFLOPS / 6 # complex128 effective
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flops = tree.total_flops()
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slices = tree.multiplicity
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est_seconds = flops * slices / (COMPLEX_FLOPS * 1e12)
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print(f"File: {path}")
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print(f"Peak memory elements: {tree.max_size():.2e}")
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print(f"Peak memory (GB): {tree.max_size() * 16 / 1e9:.2f}") # complex128 = 16 bytes
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print(f"Total FLOPs: {tree.total_flops():.2e}")
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print(f"Peak memory (GB): {tree.max_size() * 16 / 1e9:.2f}")
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print(f"Total FLOPs: {flops:.2e} x{slices} slices = {flops*slices:.2e}")
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print(f"Contraction width: {tree.contraction_width()}")
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print(f"Multiplicity (slices): {tree.multiplicity}")
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print(f"Multiplicity (slices): {slices}")
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print(f"Estimated time (96 cores): {est_seconds:.1f}s ({est_seconds/3600:.2f}h)")
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@@ -439,6 +439,7 @@ def _expectation_parallel(self, circuit, observable, method, opts):
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mpi_contract = opts.get('mpi_contract', False)
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torch_threads = opts.get('torch_threads', None)
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slicing_opts = opts.get('slicing_opts', None)
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trial_timeout = opts.get('trial_timeout', None)
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qc = self._qibo_circuit_to_quimb(
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circuit,
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@@ -472,6 +473,7 @@ def _expectation_parallel(self, circuit, observable, method, opts):
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max_time=max_time,
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n_workers=search_workers,
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slicing_opts=slicing_opts,
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trial_timeout=trial_timeout,
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)
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if tree is None:
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