The source code and dockerfile for the GSW2024 AI Lab.
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#include <assert.h>
#include <stdio.h>
#include <stdint.h>
#include <sylvan.h>
#include <sylvan_obj.hpp>
using namespace sylvan;
VOID_TASK_0(simple_cxx)
{
Bdd one = Bdd::bddOne(); // the True terminal
Bdd zero = Bdd::bddZero(); // the False terminal
// check if they really are the True/False terminal
assert(one.GetBDD() == sylvan_true);
assert(zero.GetBDD() == sylvan_false);
Bdd a = Bdd::bddVar(0); // create a BDD variable x_0
Bdd b = Bdd::bddVar(1); // create a BDD variable x_1
// check if a really is the Boolean formula "x_0"
assert(!a.isConstant());
assert(a.TopVar() == 0);
assert(a.Then() == one);
assert(a.Else() == zero);
// check if b really is the Boolean formula "x_1"
assert(!b.isConstant());
assert(b.TopVar() == 1);
assert(b.Then() == one);
assert(b.Else() == zero);
// compute !a
Bdd not_a = !a;
// check if !!a is really a
assert((!not_a) == a);
// compute a * b and !(!a + !b) and check if they are equivalent
Bdd a_and_b = a * b;
Bdd not_not_a_or_not_b = !(!a + !b);
assert(a_and_b == not_not_a_or_not_b);
// perform some simple quantification and check the results
Bdd ex = a_and_b.ExistAbstract(a); // \exists a . a * b
assert(ex == b);
Bdd andabs = a.AndAbstract(b, a); // \exists a . a * b using AndAbstract
assert(ex == andabs);
Bdd univ = a_and_b.UnivAbstract(a); // \forall a . a * b
assert(univ == zero);
// alternative method to get the cube "ab" using bddCube
BddSet variables = a * b;
std::vector<unsigned char> vec = {1, 1};
assert(a_and_b == Bdd::bddCube(variables, vec));
// test the bddCube method for all combinations
assert((!a * !b) == Bdd::bddCube(variables, std::vector<uint8_t>({0, 0})));
assert((!a * b) == Bdd::bddCube(variables, std::vector<uint8_t>({0, 1})));
assert((!a) == Bdd::bddCube(variables, std::vector<uint8_t>({0, 2})));
assert((a * !b) == Bdd::bddCube(variables, std::vector<uint8_t>({1, 0})));
assert((a * b) == Bdd::bddCube(variables, std::vector<uint8_t>({1, 1})));
assert((a) == Bdd::bddCube(variables, std::vector<uint8_t>({1, 2})));
assert((!b) == Bdd::bddCube(variables, std::vector<uint8_t>({2, 0})));
assert((b) == Bdd::bddCube(variables, std::vector<uint8_t>({2, 1})));
assert(one == Bdd::bddCube(variables, std::vector<uint8_t>({2, 2})));
}
VOID_TASK_1(_main, void*, arg)
{
// Initialize Sylvan
// With starting size of the nodes table 1 << 21, and maximum size 1 << 27.
// With starting size of the cache table 1 << 20, and maximum size 1 << 20.
// Memory usage: 24 bytes per node, and 36 bytes per cache bucket
// - 1<<24 nodes: 384 MB
// - 1<<25 nodes: 768 MB
// - 1<<26 nodes: 1536 MB
// - 1<<27 nodes: 3072 MB
// - 1<<24 cache: 576 MB
// - 1<<25 cache: 1152 MB
// - 1<<26 cache: 2304 MB
// - 1<<27 cache: 4608 MB
sylvan_set_sizes(1LL<<22, 1LL<<26, 1LL<<22, 1LL<<26);
sylvan_init_package();
// Initialize the BDD module with granularity 1 (cache every operation)
// A higher granularity (e.g. 6) often results in better performance in practice
sylvan_init_bdd();
// Now we can do some simple stuff using the C++ objects.
CALL(simple_cxx);
// Report statistics (if SYLVAN_STATS is 1 in the configuration)
sylvan_stats_report(stdout);
// And quit, freeing memory
sylvan_quit();
// We didn't use arg
(void)arg;
}
int
main (int argc, char *argv[])
{
int n_workers = 0; // automatically detect number of workers
size_t deque_size = 0; // default value for the size of task deques for the workers
size_t program_stack_size = 0; // default value for the program stack of each pthread
// Initialize the Lace framework for <n_workers> workers.
lace_init(n_workers, deque_size);
// Spawn and start all worker pthreads; suspends current thread until done.
lace_startup(program_stack_size, TASK(_main), NULL);
// The lace_startup command also exits Lace after _main is completed.
return 0;
(void)argc; // unused variable
(void)argv; // unused variable
}