Example #1
0
def fun_loops_info(fname):
    if fname in loops_info_cache:
        return loops_info_cache[fname]
    p = functions[fname].as_problem(problem.Problem)
    p.do_analysis()
    info = {}
    for l_id in p.loop_heads():
        ext_reachable = [
            n for n in p.loop_body(l_id)
            if [n2 for n2 in p.preds[n] if p.loop_id(n2) != l_id]
        ]
        if ext_reachable != [l_id]:
            trace("Loop in %s non-uniform, additional entries %s." %
                  (fname, ext_reachable))
            uniform = False
        elif problem.has_inner_loop(p, l_id):
            trace("Loop in %s non-uniform, inner loop." % fname)
            uniform = False
        else:
            assert is_addr(l_id), (fname, l_id)
            uniform = True
        for n in p.loop_body(l_id):
            info[n] = (l_id, uniform)
    loops_info_cache[fname] = info
    return info
Example #2
0
def has_complex_loop(fname):
    if fname in has_complex_loop_cache:
        return has_complex_loop_cache[fname]
    p = functions[fname].as_problem(problem.Problem)
    p.do_analysis()
    result = bool([h for h in p.loop_heads() if problem.has_inner_loop(p, h)])
    has_complex_loop_cache[fname] = result
    return result
Example #3
0
def has_complex_loop(fname):
    if fname in has_complex_loop_cache:
        return has_complex_loop_cache[fname]
    p = functions[fname].as_problem(problem.Problem)
    p.do_analysis()
    result = bool([h for h in p.loop_heads() if problem.has_inner_loop(p, h)])
    has_complex_loop_cache[fname] = result
    return result
Example #4
0
def add_fun_to_loop_data_cache(fname):
    p = functions[fname].as_problem(problem.Problem)
    p.do_loop_analysis()
    for h in p.loop_heads():
        addrs = [n for n in p.loop_body(h) if trace_refute.is_addr(n)]
        min_addr = min(addrs)
        for addr in addrs:
            addr_to_loop_id_cache[addr] = min_addr
        complex_loop_id_cache[min_addr] = problem.has_inner_loop(p, h)
    return min_addr
Example #5
0
def add_fun_to_loop_data_cache(fname):
    p = functions[fname].as_problem(problem.Problem)
    p.do_loop_analysis()
    for h in p.loop_heads():
        addrs = [n for n in p.loop_body(h) if trace_refute.is_addr(n)]
        min_addr = min(addrs)
        for addr in addrs:
            addr_to_loop_id_cache[addr] = min_addr
        complex_loop_id_cache[min_addr] = problem.has_inner_loop(p, h)
    return min_addr
Example #6
0
def get_loop_heads(fun):
    if not fun.entry:
        return []
    p = fun.as_problem(problem.Problem)
    p.do_loop_analysis()
    loops = set()
    for h in p.loop_heads():
        # any address in the loop will do. pick the smallest one
        addr = min([n for n in p.loop_body(h) if trace_refute.is_addr(n)])
        loops.add((addr, fun.name, problem.has_inner_loop(p, h)))
    return list(loops)
Example #7
0
def get_loop_heads(fun):
    if not fun.entry:
        return []
    p = fun.as_problem(problem.Problem)
    p.do_loop_analysis()
    loops = set()
    for h in p.loop_heads():
        # any address in the loop will do. pick the smallest one
        addr = min([n for n in p.loop_body(h) if trace_refute.is_addr(n)])
        loops.add((addr, fun.name, problem.has_inner_loop(p, h)))
    return list(loops)