def multiplyVectorBuff(self, vector, buffer, testing=False):
result = vec.ValueVector(self.address.nrows)
PTI.ptiOmpSparseMatrixMulVectorCSR_Reduce(result.address,
buffer.address, self.address,
vector.address)
if not testing: return result
else: PTI.ptiFreeValueVector(result.address)
def multiplyVector(self, vector, type="default", testing=False):
result = vec.ValueVector(self.address.nrows)
size = self.address.nnz
sp = size / self.address.ncols
if (type == "default"):
if (size < 6198):
PTI.ptiSparseMatrixMulVectorCSR(result.address, self.address,
vector.address)
elif (sp < 444.3):
PTI.ptiOmpSparseMatrixMulVectorCSR(result.address,
self.address,
vector.address)
else:
PTI.ptiOmpSparseMatrixMulVectorCSRReduce(
result.address, self.address, vector.address)
elif (type == "serial"):
PTI.ptiSparseMatrixMulVectorCSR(result.address, self.address,
vector.address)
elif (type == "CPU"):
PTI.ptiOmpSparseMatrixMulVectorCSR(result.address, self.address,
vector.address)
elif (type == "CPU_Buff"):
PTI.ptiOmpSparseMatrixMulVectorCSRReduce(result.address,
self.address,
vector.address)
if not testing: return result
else: PTI.ptiFreeValueVector(result.address)
def multiplyVector(self, vector, type="default", testing=False):
result = vec.ValueVector(self.address.nrows)
size = self.address.nnz
sp = size / self.address.ncols
if type == "default":
if size < 1246221: type = "serial"
elif sp < 28.8: type = "CPU"
else: type = "CPU_Buff"
if (type == "serial"):
PTI.ptiSparseMatrixMulVector(result.address, self.address,
vector.address)
elif (type == "CPU"):
PTI.ptiOmpSparseMatrixMulVector(result.address, self.address,
vector.address)
elif (type == "CPU_Buff"):
PTI.ptiOmpSparseMatrixMulVectorReduce(result.address, self.address,
vector.address)
if not testing: return result
else: PTI.ptiFreeValueVector(result.address)
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")
import HiParTIPy.Vector as vec
import sys
from time import time
name = sys.argv[1]
coo = ten.COOTensor()
coo.load(name)
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):
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
coo.multiplyVector(input_vector, testing=True)
start = time.time()
for i in range(niters):
coo.multiplyVector(input_vector, testing=True)
end = time.time()
coo.statusMatrix()
print("Time: {} sec\nniters: {}\nTime per Call: {} sec/cycle\n".format(
(end - start), niters, (end - start) / niters))