First commit

COPYING

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+Copyright (c) 2015 Marco S. Nobile (Department of Informatics,
+Systems and Communication, University of Milano-Bicocca).
+All rights reserved.
+
+Permission is hereby granted, without written agreement and without
+license or royalty fees, to use, copy, modify, and distribute this
+software and its documentation for any purpose, provided that the
+above copyright notice and the following two paragraphs appear in all
+copies of this software.
+
+IN NO EVENT SHALL THE AUTHOR(S) BE LIABLE TO ANY PARTY FOR DIRECT,
+INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES ARISING OUT OF
+THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE AUTHOR(S),
+HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+THE DEPARTMENT OF INFORMATICS, SYSTEMS AND COMMUNICATION SPECIFICALLY 
+DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. 
+THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE 
+AUTHOR(S) HAVE NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES,
+ENHANCEMENTS, OR MODIFICATIONS.
+
+Contact: [email protected]

README.markdown

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+#cupSODA release 1.0
+
+## ABOUT
+
+cupSODA is a black-box deterministic simulator of biological systems that exploits the remarkable memory bandwidth and computational capability of GPUs. 
+cupSODA allows to efficiently execute in parallel large numbers of simulations, which are usually required to investigate the emergent dynamics of a given biological system under different conditions.
+cupSODA works by automatically deriving the system of ordinary differential equations from a reaction-based mechanistic model, defined according to the mass-action kinetics, and then exploiting the numerical integration algorithm, LSODA. 
+
+
+## DEPENDENCIES
+
+Just the Nvidia CUDA library.
+
+
+## LICENSE
+
+BSD License
+
+
+## CONTACT 
+
+[email protected]

compile.sh

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+#!/bin/bash
+module load cuda
+nvcc kernel.cu cupSODA.cu input_reader.cpp stoc2det.cpp -gencode=arch=compute_20,code=compute_20 -O3 -o cupSODA --use_fast_math --cudart static
+nvcc kernel.cu cupSODA.cu input_reader.cpp stoc2det.cpp -gencode=arch=compute_35,code=compute_35 -O3 -o cupSODA35 --use_fast_math  --cudart static
+
+

constants.h

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+/*
+Constants and defines used by cupSODA.
+See file COPYING for copyright and licensing information.
+*/
+
+
+#ifndef __CONSTANTS__
+#define __CONSTANTS
+
+/* cuLSODO variables */
+// #define THREADS	16
+// #define BLOCKS 1
+// #define VARIABLES 4
+// #define KINCONSTANTS 3
+
+#define USE_SHARED_MEMORY
+#define USE_CONSTANT_MEMORY
+
+#define ERROR_INSUFF_CONSTANT_MEMORY_ODE 100
+#define ERROR_INSUFF_CONSTANT_MEMORY_JAC 101
+#define ERROR_INSUFF_SHARED_MEMORY		 102
+#define ERROR_INSUFF_GLOBAL_MEMORY	     103
+#define ERROR_TIMESERIES_NOT_SPECIFIED   1001
+
+#endif

create_condition.py

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+import locale
+import numpy
+
+path= "input_MM"
+
+tpb = 64
+blocks = 64
+points = 1000
+threads = tpb*blocks
+print "Total threads:", threads
+EPSILON = 10E-2
+SIZEOF_FLOAT = 4
+specie = 0
+PSA_QTY = False
+
+def intWithCommas(x):
+    if type(x) not in [type(0), type(0L)]:
+        raise TypeError("Parameter must be an integer.")
+    if x < 0:
+        return '-' + intWithCommas(-x)
+    result = ''
+    while x >= 1000:
+        x, r = divmod(x, 1000)
+        result = "'%03d%s" % (r, result)
+    return "%d%s" % (x, result)
+
+
+M_0 = []
+with open(path+"/M_0") as f:
+	M_0  = f.readline();
+	specie = len(M_0.split())
+	if not PSA_QTY:
+		with open(path+"/MX_0", "w") as f2:
+			for i in range(threads):
+				f2.write(M_0)
+
+specie = 1
+
+lista_parametri = []
+with open(path+"/c_vector") as f:
+	for line in f:
+		lista_parametri.append( float( line.strip("\n") ))
+with open(path+"/c_matrix", "w") as f2:
+	for i in range(threads):
+		for j in lista_parametri[:-1]:
+			f2.write(str(j)+"\t")
+		f2.write(str(lista_parametri[-1]))
+		if i!=threads-1:
+			f2.write("\n")
+
+lista_campioni = []
+with open(path+"/time_max") as f:
+	tempo = float(f.readline())
+	tempo = tempo-EPSILON
+	lista_campioni = numpy.linspace(EPSILON,tempo,points)
+	print "Requested samples:", len(lista_campioni)
+with open(path+"/t_vector", "w") as f2:
+	for c in lista_campioni:
+		f2.write(str(c)+"\n")
+
+print "Memoria necessaria per lettura output completo:", intWithCommas(threads*points*SIZEOF_FLOAT*specie), "bytes"