import time as time
import sys
sys.path.insert(0, "./")
import HiParTIPy.Matrix as ptiMat
if len(sys.argv) < 2:
sys.exit("Usage: python3 benchmarkPy/matrix/sort.py [.mtx]")
mtxname = sys.argv[1]
print("Load Matrix from: {}".format(mtxname))
coo_in = ptiMat.COOMatrix()
coo_in.loadMatrix(mtxname)
coo_in.statusMatrix()
# Reordering in Lexi-order
coo_in.reorder(type="lexi")
# Reordering in random order
coo_in.reorder(type="random")
import time as time
import sys
sys.path.insert(0, "./")
import HiParTIPy.Matrix as ptiMat
if len(sys.argv) < 2:
sys.exit("Usage: python3 benchmarkPy/matrix/spmm.py [.mtx] [ncols] [niters]")
mtxname = sys.argv[1]
print("Load Matrix from: {}".format(mtxname))
R = int(sys.argv[2]) # Specify number of columns for the dense matrix
if R==0: R=ncols
niters = int(sys.argv[3]) # Specify number of iterations
coo = ptiMat.COOMatrix()
coo.loadMatrix(mtxname) # Specify what matrix to use
sb_bits = 7
hicoo = coo.convert(type="hicoo", blockbits=sb_bits, superblockbits=sb_bits) # Specify blocking for hicoo matricies
csr = coo.convert(type="csr")
ncols = coo.ncols()
nrows = coo.nrows()
nnz = coo.nnz()
input_mat = ptiMat.DenseMatrix(ncols, R)
input_mat.randomMatrix()
######## COO-SpMM #########
# warm-up
coo.multiplyMatrix(input_mat,testing=True)
import HiParTIPy.Matrix as mat
import HiParTIPy.Vector as vec
import HiParTIPy.Buffers as buff
coo = mat.COOMatrix()
coo.loadMatrix("data/matrices/tiny.mtx")
hicoo = coo.convertToHiCOO()
print(coo.ncols())
vec = vec.ValueVector(coo.ncols())
vec.makeRandom()
buf = buff.VecBuff(coo.ncols())
print("HERE")
coo.multiplyVector(vec)
print("HREE")
hicoo.multiplyVectorBuff(vec,buf)
print("HERE")
buf.free()
print("HERE")
print("File Name: {}".format(name))
niters = int(sys.argv[2])
equ = int(niters / 100)
mode = int(sys.argv[3])
vector = vec.ValueVector(coo.address.ndims[mode])
for i in range(equ):
coo.mulVector(vector, mode, testing=True)
start = time()
for i in range(niters):
coo.mulVector(vector, mode, testing=True)
end = time()
print("MulVector: Time = {},\n Time per Cycles = {}".format(
end - start, (end - start) / niters))
var = sys.argv[4]
matrix = mat.DenseMatrix(coo.address.ndims[mode], var)
for i in range(equ):
coo.mulMatrix(matrix, mode, testing=True)
start = time()
for i in range(niters):
coo.mulMatrix(matrix, mode, testing=True)
end = time()
print("MulMatrix: Time = {},\n Time per Cycles = {}".format(
end - start, (end - start) / niters))
import HiParTIPy.Matrix as ptiMat
if len(sys.argv) < 2:
sys.exit(
"Usage: python3 benchmarkPy/tensor/mttkrp.py [.tns] [mode] [rank] [niters]"
)
name = sys.argv[1]
mode = sys.argv[2]
R = int(sys.argv[3])
niters = int(sys.argv[4])
print("Load Tensor from: {}".format(name))
coo = ptiTen.COOTensor()
coo.load(name)
nmodes = coo.nmodes()
ndims_mode = coo.dim_mode(mode)
input_mat = ptiMat.DenseMatrix(ndims_mode, R)
input_mat.randomMatrix()
coo.mulMatrix(mats, mode, type='serial', testing=True)
start = time()
for i in range(niters):
coo.mulMatrix(mats, mode, type='serial', testing=True)
end = time()
print("TTM: Time = {},\n Time per Cycles = {}".format(end - start,
(end - start) / niters))
hicoo = coo.toHiCOO()
import time as time
import sys
sys.path.insert(0, "./")
import HiParTIPy.Matrix as ptiMat
import HiParTIPy.Vector as ptiVec
if len(sys.argv) < 2:
sys.exit("Usage: python3 benchmarkPy/matrix/spmv.py [.mtx] [niters]")
mtxname = sys.argv[1]
print("Load Matrix from: {}".format(mtxname))
niters = int(sys.argv[2]) # Specify number of iterations
coo = ptiMat.COOMatrix()
coo.loadMatrix(mtxname) # Specify what matrix to use.
sb_bits = 7
hicoo = coo.convert(
type="hicoo", blockbits=sb_bits,
superblockbits=sb_bits) # Specify blocking for hicoo matricies
csr = coo.convert(type="csr")
ncols = coo.ncols()
nrows = coo.nrows()
nnz = coo.nnz()
input_vector = ptiVec.ValueVector(ncols)
input_vector.makeRandom()
######## COO-SpMV #########
# warm-up