target_list, target_index_list, target_nmr_list = new_read_database( target_filename) target_outdic = {'nmr': target_nmr_list[target_index]} target_mol = target_list[target_index] if __name__ == "__main__": comm = MPI.COMM_WORLD size = comm.size rank = comm.rank status = MPI.Status() READY, START, DONE, EXIT = 0, 1, 2, 3 val = [ '\n', '&', 'O', 'c', '1', '(', ')', '=', 'C', 'N', '#', 'n', '2', 'o', '3', '-', '4' ] chem_model = loaded_model() graph = tf.get_default_graph() chemical_state = chemical() ts_strategy = cnf.get('param', 'ts_strategy') #'uct', 'puct' search_parameter = float( cnf.get('param', 'search_parameter') ) #If ts_strategy=='uct', 0 < search_parameter < 1. If ts_strategy=='puct', default value is 5 (AlphaGo). num_simulations = int(cnf.get( 'param', 'num_simulations')) # core - 1, max: 2560 (skylake) gau_parallel = 1 num_rollout = int(cnf.get('param', 'num_rollout')) simulation_time = 3600 * int(cnf.get( 'param', 'simulation_time')) # 3600*24 # max: 168h trie = int(cnf.get('param', 'trie')) random_trie = int(cnf.get('param', 'random_trie')) alpha = 1 # alph*mean + (1 - alpha)*max + bais
all_com = [] all_score = [] val_score = [] load_bal = [] sim_time = [] lock = Lock() stored_jobs = [] coll = [] exp_time = [] print("check all ranks:", rank) """ start distributing jobs to all ranks """ graph = tf.get_default_graph() #graph.finalize() model = loaded_model() model._make_predict_function() mem = np.zeros(1024 * 10 * 1024) #8192) MPI.Attach_buffer(mem) num_cores = 8 #q1=Queue() num_job = num_cores random.seed(1) hsm = HashTable() #hsm=comm.bcast(hsm,root=0) if rank == 0: _, rootdest = hsm.hashing(['&']) #print ("rootdest:",rootdest) for i in range(num_job): comm.bsend(rootnode, dest=rootdest, tag=0)