diff --git a/examples/python/ispc-harness.py b/examples/python/ispc-harness.py
index 7b29340cf2ea73b3afb726da6fb81799ab3c5c2d..f18bc1c4bb9e5cf6f82ed0506a96b0a3924194dc 100644
--- a/examples/python/ispc-harness.py
+++ b/examples/python/ispc-harness.py
@@ -62,6 +62,8 @@ def build_ispc_shared_lib(
# }}}
+# {{{ numpy address munging
+
def address_from_numpy(obj):
ary_intf = getattr(obj, "__array_interface__", None)
if ary_intf is None:
@@ -111,38 +113,101 @@ def empty_aligned(shape, dtype, order='C', n=64):
return array
+# }}}
+
+
+def transform(knl, vars, stream_dtype):
+ vars = [v.strip() for v in vars.split(",")]
+ knl = lp.assume(knl, "n>0")
+ knl = lp.split_iname(
+ knl, "i", 2**18, outer_tag="g.0", slabs=(0, 1))
+ knl = lp.split_iname(knl, "i_inner", 8, inner_tag="l.0")
+
+ knl = lp.add_and_infer_dtypes(knl, {
+ var: stream_dtype
+ for var in vars
+ })
+
+ knl = lp.set_argument_order(knl, vars + ["n"])
+
+ return knl
+
+
+def gen_code(knl):
+ knl = lp.preprocess_kernel(knl)
+ knl = lp.get_one_scheduled_kernel(knl)
+ ispc_code, arg_info = lp.generate_code(knl)
+
+ return ispc_code
+
+
+NRUNS = 10
+ALIGN_TO = 4096
+ARRAY_SIZE = 2**28
+
+if 0:
+ STREAM_DTYPE = np.float64
+ STREAM_CTYPE = ctypes.c_double
+else:
+ STREAM_DTYPE = np.float32
+ STREAM_CTYPE = ctypes.c_float
+
+if 1:
+ INDEX_DTYPE = np.int32
+ INDEX_CTYPE = ctypes.c_int
+else:
+ INDEX_DTYPE = np.int64
+ INDEX_CTYPE = ctypes.c_longlong
+
def main():
with open("tasksys.cpp", "r") as ts_file:
tasksys_source = ts_file.read()
- stream_dtype = np.float64
- stream_ctype = ctypes.c_double
- index_dtype = np.int32
-
- from loopy.target.ispc import ISPCTarget
- stream_knl = lp.make_kernel(
- "{[i]: 0<=i<n}",
- "z[i] = x[i] + a*y[i]",
- target=ISPCTarget(),
- index_dtype=index_dtype)
-
- stream_knl = lp.add_and_infer_dtypes(stream_knl, {
- "a": stream_dtype,
- "x": stream_dtype,
- "y": stream_dtype
- })
-
- stream_knl = lp.assume(stream_knl, "n>0")
- stream_knl = lp.split_iname(stream_knl,
- "i", 2**18, outer_tag="g.0", slabs=(0, 1))
- stream_knl = lp.split_iname(stream_knl, "i_inner", 8, inner_tag="l.0")
- stream_knl = lp.preprocess_kernel(stream_knl)
- stream_knl = lp.get_one_scheduled_kernel(stream_knl)
- stream_knl = lp.set_argument_order(stream_knl, "n,a,x,y,z")
- ispc_code, arg_info = lp.generate_code(stream_knl)
+ if 0:
+ from loopy.target.ispc import ISPCTarget
+ stream_knl = lp.make_kernel(
+ "{[i]: 0<=i<n}",
+ "z[i] = x[i] + a*y[i]",
+ target=ISPCTarget(),
+ index_dtype=INDEX_DTYPE)
+
+ stream_knl = lp.add_and_infer_dtypes(stream_knl, {
+ "a": STREAM_DTYPE,
+ "x": STREAM_DTYPE,
+ "y": STREAM_DTYPE
+ })
+
+ stream_knl = lp.assume(stream_knl, "n>0")
+ stream_knl = lp.split_iname(stream_knl,
+ "i", 2**18, outer_tag="g.0", slabs=(0, 1))
+ stream_knl = lp.split_iname(stream_knl, "i_inner", 8, inner_tag="l.0")
+ stream_knl = lp.preprocess_kernel(stream_knl)
+ stream_knl = lp.get_one_scheduled_kernel(stream_knl)
+ stream_knl = lp.set_argument_order(stream_knl, "n,a,x,y,z")
+ ispc_code, arg_info = lp.generate_code(stream_knl)
+
+ def make_knl(name, insn, vars):
+ knl = lp.make_kernel(
+ "{[i]: 0<=i<n}",
+ insn,
+ target=lp.ISPCTarget(), index_dtype=INDEX_DTYPE,
+ name="stream_"+name+"_tasks")
+
+ knl = transform(knl, vars, STREAM_DTYPE)
+ return knl
+
+ init_knl = make_knl("init", """
+ a[i] = 1
+ b[i] = 2
+ c[i] = 0
+ """, "a,b,c")
+ triad_knl = make_knl("triad", """
+ a[i] = b[i] + scalar * c[i]
+ """, "a,b,c,scalar")
with TemporaryDirectory() as tmpdir:
+ ispc_code = gen_code(init_knl) + gen_code(triad_knl)
print(ispc_code)
build_ispc_shared_lib(
@@ -157,7 +222,7 @@ def main():
#"--opt=fast-math",
#"--opt=disable-fma",
]
- + (["--addressing=64"] if index_dtype == np.int64 else [])
+ + (["--addressing=64"] if INDEX_DTYPE == np.int64 else [])
),
ispc_bin="/home/andreask/pack/ispc-v1.9.0-linux/ispc",
quiet=False,
@@ -165,46 +230,51 @@ def main():
knl_lib = ctypes.cdll.LoadLibrary(os.path.join(tmpdir, "shared.so"))
- n = 2**28
- a = 5
+ scalar = 5
- align_to = 64
- x = empty_aligned(n, dtype=stream_dtype, n=align_to)
- y = empty_aligned(n, dtype=stream_dtype, n=align_to)
- z = empty_aligned(n, dtype=stream_dtype, n=align_to)
+ a = empty_aligned(ARRAY_SIZE, dtype=STREAM_DTYPE, n=ALIGN_TO)
+ b = empty_aligned(ARRAY_SIZE, dtype=STREAM_DTYPE, n=ALIGN_TO)
+ c = empty_aligned(ARRAY_SIZE, dtype=STREAM_DTYPE, n=ALIGN_TO)
print(
- hex(address_from_numpy(x)),
- hex(address_from_numpy(y)),
- hex(address_from_numpy(z)))
- assert address_from_numpy(x) % align_to == 0
- assert address_from_numpy(y) % align_to == 0
- assert address_from_numpy(z) % align_to == 0
-
- nruns = 10
+ hex(address_from_numpy(a)),
+ hex(address_from_numpy(b)),
+ hex(address_from_numpy(c)))
+ assert address_from_numpy(a) % ALIGN_TO == 0
+ assert address_from_numpy(b) % ALIGN_TO == 0
+ assert address_from_numpy(c) % ALIGN_TO == 0
+
+ knl_lib.stream_init_tasks(
+ cptr_from_numpy(a),
+ cptr_from_numpy(b),
+ cptr_from_numpy(c),
+ INDEX_CTYPE(ARRAY_SIZE),
+ )
def call_kernel():
- knl_lib.loopy_kernel(
- ctypes.c_int(n), stream_ctype(a),
- cptr_from_numpy(x),
- cptr_from_numpy(y),
- cptr_from_numpy(z))
+ knl_lib.stream_triad_tasks(
+ cptr_from_numpy(a),
+ cptr_from_numpy(b),
+ cptr_from_numpy(c),
+ STREAM_CTYPE(scalar),
+ INDEX_CTYPE(ARRAY_SIZE),
+ )
call_kernel()
call_kernel()
start_time = time()
- for irun in range(nruns):
+ for irun in range(NRUNS):
call_kernel()
elapsed = time() - start_time
- print(elapsed/nruns)
+ print(elapsed/NRUNS)
- print(1e-9 * 3 * x.nbytes * nruns / elapsed, "GB/s")
+ print(1e-9*3*a.nbytes*NRUNS/elapsed, "GB/s")
- assert la.norm(z-a*x+y) < 1e-10
+ assert la.norm(a-b+scalar*c, np.inf) < np.finfo(STREAM_DTYPE).eps * 10
if __name__ == "__main__":