from openpower.decoder.isa.test_caller import run_tst
from openpower.sv.trans.svp64 import SVP64Asm
from copy import deepcopy
-from openpower.decoder.helpers import fp64toselectable
+from openpower.decoder.helpers import fp64toselectable, SINGLE
from openpower.decoder.isafunctions.double2single import DOUBLE2SINGLE
-def transform_radix2(vec, exptable):
+def transform_radix2(vec, exptable, reverse=False):
"""
# FFT and convolution test (Python), based on Project Nayuki
#
levels = n.bit_length() - 1
# Copy with bit-reversed permutation
- #vec = [vec[reverse_bits(i, levels)] for i in range(n)]
+ if reverse:
+ vec = [vec[reverse_bits(i, levels)] for i in range(n)]
size = 2
while size <= n:
return vec
-def transform_radix2_complex(vec_r, vec_i, cos_r, sin_i):
+def transform_radix2_complex(vec_r, vec_i, cos_r, sin_i, reverse=False):
"""
# FFT and convolution test (Python), based on Project Nayuki
#
levels = n.bit_length() - 1
# Copy with bit-reversed permutation
- #vec = [vec[reverse_bits(i, levels)] for i in range(n)]
+ if reverse:
+ vec = [vec[reverse_bits(i, levels)] for i in range(n)]
size = 2
while size <= n:
def test_sv_remap_fpmadds_fft(self):
""">>> lst = ["svshape 8, 1, 1, 1, 0",
- "svremap 31, 1, 0, 2, 0, 1",
+ "svremap 31, 1, 0, 2, 0, 1, 0",
"sv.ffmadds 2.v, 2.v, 2.v, 10.v"
]
runs a full in-place O(N log2 N) butterfly schedule for
(3 inputs, 2 outputs)
"""
lst = SVP64Asm( ["svshape 8, 1, 1, 1, 0",
- "svremap 31, 1, 0, 2, 0, 1",
+ "svremap 31, 1, 0, 2, 0, 1, 0",
"sv.ffmadds 0.v, 0.v, 0.v, 8.v"
])
lst = list(lst)
def test_sv_remap_fpmadds_fft_svstep(self):
""">>> lst = SVP64Asm( [
"svshape 8, 1, 1, 1, 1",
- "svremap 31, 1, 0, 2, 0, 1",
+ "svremap 31, 1, 0, 2, 0, 1, 0",
"sv.ffmadds 0.v, 0.v, 0.v, 8.v",
"setvl. 0, 0, 1, 1, 0, 0",
- "bc 4, 2, -16"
+ "bc 6, 3, -16"
])
runs a full in-place O(N log2 N) butterfly schedule for
Discrete Fourier Transform. this version however uses
"""
lst = SVP64Asm( [
"svshape 8, 1, 1, 1, 1",
- "svremap 31, 1, 0, 2, 0, 1",
+ "svremap 31, 1, 0, 2, 0, 1, 0",
"sv.ffmadds 0.v, 0.v, 0.v, 8.v",
"setvl. 0, 0, 1, 1, 0, 0",
- "bc 4, 2, -16"
+ "bc 6, 3, -16"
])
lst = list(lst)
# SVSTATE (calculated VL)
svstate = SVP64State()
- svstate.vl[0:7] = VL # VL
- svstate.maxvl[0:7] = VL # MAXVL
- print ("SVSTATE", bin(svstate.spr.asint()))
+ svstate.vl = VL # VL
+ svstate.maxvl = VL # MAXVL
+ print ("SVSTATE", bin(svstate.asint()))
with Program(lst, bigendian=False) as program:
sim = self.run_tst_program(program, svstate=svstate,
""">>> lst = SVP64Asm( [
"svshape 8, 1, 1, 1, 1",
# RA: jh (S1) RB: n/a RC: k (S2) RT: scalar EA: n/a
- "svremap 5, 1, 0, 2, 0, 0",
+ "svremap 5, 1, 0, 2, 0, 0, 1",
"sv.fmuls 24, 0.v, 8.v",
# RA: scal RB: jl (S0) RC: n/a RT: jl (S0) EA: jh (S1)
- "svremap 26, 0, 0, 0, 0, 1",
+ "svremap 26, 0, 0, 0, 0, 1, 1",
"sv.ffadds 0.v, 24, 0.v",
"setvl. 0, 0, 1, 1, 0, 0",
- "bc 4, 2, -28"
+ "bc 6, 3, -28"
])
runs a full in-place O(N log2 N) butterfly schedule for
twin-add: # sv.ffadds FRT(/FRS), FRA, FRB
vec[jh] = temp2 - temp1
vec[jl] = temp2 + temp1
+
+ also see notes in complex fft test: here svremap is done in
+ "non-persistent" mode (as a demo) whereas in the complex fft
+ svremap is used in "persistent" mode, where by a complete
+ coincidence the REMAP arguments all happen to line up and
+ only one persistent svremap is needed. the exact same trick
+ *could* be applied here but for illustrative purposes it is not.
"""
lst = SVP64Asm( [
"svshape 8, 1, 1, 1, 1",
# RA: jh (S1) RB: n/a RC: k (S2) RT: scalar EA: n/a
- "svremap 5, 1, 0, 2, 0, 0",
+ "svremap 5, 1, 0, 2, 0, 0, 0",
"sv.fmuls 24, 0.v, 8.v",
# RA: scal RB: jl (S0) RC: n/a RT: jl (S0) EA: jh (S1)
- "svremap 26, 0, 0, 0, 0, 1",
+ "svremap 26, 0, 0, 0, 0, 1, 0",
"sv.ffadds 0.v, 24, 0.v",
"setvl. 0, 0, 1, 1, 0, 0",
- "bc 4, 2, -28"
+ "bc 6, 3, -28"
])
lst = list(lst)
# SVSTATE (calculated VL)
svstate = SVP64State()
- svstate.vl[0:7] = VL # VL
- svstate.maxvl[0:7] = VL # MAXVL
- print ("SVSTATE", bin(svstate.spr.asint()))
+ svstate.vl = VL # VL
+ svstate.maxvl = VL # MAXVL
+ print ("SVSTATE", bin(svstate.asint()))
with Program(lst, bigendian=False) as program:
sim = self.run_tst_program(program, svstate=svstate,
sv.ffmadds FRT, FRA, FRC, FRB actually does:
fmadds FRT , FRA, FRC, FRA
fnmsubs FRT+vl, FRA, FRC, FRB+vl
+
"""
lst = SVP64Asm(["sv.ffmadds 2.v, 2.v, 2.v, 10.v"
])
# SVSTATE (in this case, VL=2)
svstate = SVP64State()
- svstate.vl[0:7] = 4 # VL
- svstate.maxvl[0:7] = 4 # MAXVL
- print ("SVSTATE", bin(svstate.spr.asint()))
+ svstate.vl = 4 # VL
+ svstate.maxvl = 4 # MAXVL
+ print ("SVSTATE", bin(svstate.asint()))
with Program(lst, bigendian=False) as program:
sim = self.run_tst_program(program, svstate=svstate,
# SVSTATE (in this case, VL=2)
svstate = SVP64State()
- svstate.vl[0:7] = 4 # VL
- svstate.maxvl[0:7] = 4 # MAXVL
- print ("SVSTATE", bin(svstate.spr.asint()))
+ svstate.vl = 4 # VL
+ svstate.maxvl = 4 # MAXVL
+ print ("SVSTATE", bin(svstate.asint()))
with Program(lst, bigendian=False) as program:
sim = self.run_tst_program(program, svstate=svstate,
temp2 = vec[jl]
vec[jh] = temp2 - temp1
vec[jl] = temp2 + temp1
+
+ note: a rather nice convenience / coincidence. the meaning of
+ these two instructions is:
+ # RA: jh (S1) RB: n/a RC: k (S2) RT: scalar EA: n/a
+ "svremap 5, 1, 0, 2, 0, 0, 1",
+ # RA: scal RB: jl (S0) RC: n/a RT: jl (S0) EA: jh (S1)
+ "svremap 26, 0, 0, 0, 0, 1, 1",
+
+ however it turns out that they can be *merged*, and for
+ the first one (sv.fmadds/sv.fmsubs) the scalar arguments (RT, RB)
+ *ignore* their REMAPs (by definition, because you can't REMAP
+ scalar operands), and for the second one (sv.ffads) exactly the
+ right REMAPs are also ignored!
+
+ therefore we can merge:
+ "svremap 5, 1, 0, 2, 0, 0, 1",
+ "svremap 26, 0, 0, 0, 0, 1, 1",
+ into:
+ "svremap 31, 1, 0, 2, 0, 1, 1",
+ and save one instruction.
"""
lst = SVP64Asm( [
- # set triple butterfly mode
+ # set triple butterfly mode with persistent "REMAP"
"svshape 8, 1, 1, 1, 1",
+ "svremap 31, 1, 0, 2, 0, 1, 1",
# tpre
- "svremap 5, 1, 0, 2, 0, 0",
"sv.fmuls 24, 0.v, 16.v", # mul1_r = r*cos_r
- "svremap 5, 1, 0, 2, 0, 0",
- "sv.fmuls 25, 8.v, 20.v", # mul2_r = i*sin_i
- "fadds 24, 24, 25", # tpre = mul1_r + mul2_r
+ "sv.fmadds 24, 8.v, 20.v, 24", # mul2_r = i*sin_i
+ # tpre = mul1_r + mul2_r
# tpim
- "svremap 5, 1, 0, 2, 0, 0",
"sv.fmuls 26, 0.v, 20.v", # mul1_i = r*sin_i
- "svremap 5, 1, 0, 2, 0, 0",
- "sv.fmuls 27, 8.v, 16.v", # mul2_i = i*cos_r
- "fsubs 26, 27, 26", # tpim = mul2_i - mul1_i
+ "sv.fmsubs 26, 8.v, 16.v, 26", # mul2_i = i*cos_r
+ # tpim = mul2_i - mul1_i
# vec_r jh/jl
- "svremap 26, 0, 0, 0, 0, 1",
"sv.ffadds 0.v, 24, 0.v", # vh/vl +/- tpre
# vec_i jh/jl
- "svremap 26, 0, 0, 0, 0, 1",
"sv.ffadds 8.v, 26, 8.v", # vh/vl +- tpim
# svstep loop
"setvl. 0, 0, 1, 1, 0, 0",
- "bc 4, 2, -84"
+ "bc 6, 3, -56"
])
lst = list(lst)
# SVSTATE (calculated VL)
svstate = SVP64State()
- svstate.vl[0:7] = VL # VL
- svstate.maxvl[0:7] = VL # MAXVL
- print ("SVSTATE", bin(svstate.spr.asint()))
+ svstate.vl = VL # VL
+ svstate.maxvl = VL # MAXVL
+ print ("SVSTATE", bin(svstate.asint()))
with Program(lst, bigendian=False) as program:
sim = self.run_tst_program(program, svstate=svstate,
# SVSTATE (in this case, VL=2)
svstate = SVP64State()
- svstate.vl[0:7] = 4 # VL
- svstate.maxvl[0:7] = 4 # MAXVL
- print ("SVSTATE", bin(svstate.spr.asint()))
+ svstate.vl = 4 # VL
+ svstate.maxvl = 4 # MAXVL
+ print ("SVSTATE", bin(svstate.asint()))
with Program(lst, bigendian=False) as program:
sim = self.run_tst_program(program, svstate=svstate,
self.assertEqual(sim.fpr(i+2), t)
self.assertEqual(sim.fpr(i+6), u)
+ def test_sv_remap_fpmadds_fft_ldst(self):
+ """>>>lst = ["setvl 0, 0, 8, 0, 1, 1",
+ "sv.lfssh 0.v, 4(0), 20", # bit-reversed
+ "svshape 8, 1, 1, 1, 0",
+ "svremap 31, 1, 0, 2, 0, 1, 0",
+ "sv.ffmadds 0.v, 0.v, 0.v, 8.v"
+
+ runs a full in-place O(N log2 N) butterfly schedule for
+ Discrete Fourier Transform, using bit-reversed LD/ST
+ """
+ lst = SVP64Asm( ["svshape 8, 1, 1, 15, 0",
+ "svremap 1, 0, 0, 0, 0, 0, 0, 0",
+ "sv.lfssh 0.v, 4(0), 20", # shifted
+ "svshape 8, 1, 1, 1, 0",
+ "svremap 31, 1, 0, 2, 0, 1, 0",
+ "sv.ffmadds 0.v, 0.v, 0.v, 8.v"
+ ])
+ lst = list(lst)
+
+ # array and coefficients to test
+ av = [7.0, -9.8, 3.0, -32.3,
+ -2.0, 5.0, -9.8, 31.3] # array 0..7
+ coe = [-0.25, 0.5, 3.1, 6.2] # coefficients
+
+ # store in regfile
+ fprs = [0] * 32
+ for i, c in enumerate(coe):
+ fprs[i+8] = fp64toselectable(c)
+ # store in memory
+ mem = {}
+ val = 0
+ for i, a in enumerate(av):
+ a = SINGLE(fp64toselectable(a)).value
+ shift = (i % 2) == 1
+ if shift == 0:
+ val = a
+ else:
+ mem[(i//2)*8] = val | (a << 32)
+
+ with Program(lst, bigendian=False) as program:
+ sim = self.run_tst_program(program, initial_mem=mem,
+ initial_fprs=fprs)
+ print ("spr svshape0", sim.spr['SVSHAPE0'])
+ print (" xdimsz", sim.spr['SVSHAPE0'].xdimsz)
+ print (" ydimsz", sim.spr['SVSHAPE0'].ydimsz)
+ print (" zdimsz", sim.spr['SVSHAPE0'].zdimsz)
+ print ("spr svshape1", sim.spr['SVSHAPE1'])
+ print ("spr svshape2", sim.spr['SVSHAPE2'])
+ print ("spr svshape3", sim.spr['SVSHAPE3'])
+
+ print ("mem dump")
+ print (sim.mem.dump())
+
+ # work out the results with the twin mul/add-sub,
+ # note bit-reverse mode requested
+ res = transform_radix2(av, coe, reverse=True)
+
+ for i, expected in enumerate(res):
+ print ("i", i, float(sim.fpr(i)), "expected", expected)
+ for i, expected in enumerate(res):
+ # convert to Power single
+ expected = DOUBLE2SINGLE(fp64toselectable(expected))
+ expected = float(expected)
+ actual = float(sim.fpr(i))
+ # approximate error calculation, good enough test
+ # reason: we are comparing FMAC against FMUL-plus-FADD-or-FSUB
+ # and the rounding is different
+ err = abs(actual - expected) / expected
+ self.assertTrue(err < 1e-6)
+
def run_tst_program(self, prog, initial_regs=None,
svstate=None,
initial_mem=None,