<reponame>xdata-skylark/libskylark
#!/usr/bin/env python
# MPI usage:
# mpiexec -np 2 python skylark/examples/example_sketch.py

# prevent mpi4py from calling MPI_Finalize()
import mpi4py.rc
mpi4py.rc.finalize   = False

import El
from skylark import sketch, elemhelper
from mpi4py import MPI
import numpy as np
import time

# Configuration
m = 20000;
n = 300;
t = 1000;
#sketches = { "JLT" : sketch.JLT, "FJLT" : sketch.FJLT, "CWT" : sketch.CWT }
sketches = { "JLT" : sketch.JLT, "CWT" : sketch.CWT }

# Set up the random regression problem.
A = El.DistMatrix((El.dTag, El.VR, El.STAR))
El.Uniform(A, m, n)
b = El.DistMatrix((El.dTag, El.VR, El.STAR))
El.Uniform(b, m, 1)

# Solve using Elemental
# Elemental currently does not support LS on VR,STAR.
# So we copy.
A1 = El.DistMatrix()
El.Copy(A, A1)
b1 = El.DistMatrix()
El.Copy(b, b1)
x = El.DistMatrix(El.dTag, El.MC, El.MR)
El.Uniform(x, n, 1)
t0 = time.time()
El.LeastSquares(A1, b1, El.NORMAL, x)
telp = time.time() - t0

# Compute residual
r = El.DistMatrix()
El.Copy(b, r)
El.Gemv(El.NORMAL, -1.0, A1, x, 1.0, r)
res = El.Norm(r)
if (MPI.COMM_WORLD.Get_rank() == 0):
  print "Exact solution residual %(res).3f\t\t\ttook %(elp).2e sec" % \
      { "res" : res, "elp": telp }

# Lower-layers are automatically initilalized when you import Skylark,
# It will use system time to generate the seed. However, we can
# reinitialize for so to fix the seed.
sketch.initialize(123834);

#
# Solve the problem using sketching
#
for sname in sketches:
  stype = sketches[sname]

  t0 = time.time()

  # Create transform.
  S = stype(m, t, defouttype="SharedMatrix")

  # Sketch both A and b using the same sketch
  SA = S * A
  Sb = S * b

  # SA and Sb reside on rank zero, so solving the equation is
  # done there.
  if (MPI.COMM_WORLD.Get_rank() == 0):
    # Solve using NumPy
    [x, res, rank, s] = np.linalg.lstsq(SA.Matrix().ToNumPy(), Sb.Matrix().ToNumPy())
  else:
    x = None

  telp = time.time() - t0

  # Distribute the solution so to compute residual in a distributed fashion
  x = MPI.COMM_WORLD.bcast(x, root=0)

  # Convert x to a distributed matrix.
  # Here we give the type explictly, but the value used is the default.
  x = elemhelper.local2distributed(x, type=El.DistMatrix)

  # Compute residual
  r = El.DistMatrix()
  El.Copy(b, r)
  El.Gemv(El.NORMAL, -1.0, A1, x, 1.0, r)
  res = El.Norm(r)
  if (MPI.COMM_WORLD.Get_rank() == 0):
    print "%(name)s:\tSketched solution residual %(val).3f\ttook %(elp).2e sec" %\
        {"name" : sname, "val" : res, "elp" : telp}

  # As with all Python object they will be automatically garbage
  # collected, and the associated memory will be freed.
  # You can also explicitly free them.
  del S     # S = 0 will also free memory.

# Really no need to "close" the lower layers -- it will do it automatically.
# However, if you really want to you can do it.
sketch.finalize()



#!/usr/bin/env python
# MPI usage:
# mpiexec -np 2 python skylark/examples/example_sketch.py

# prevent mpi4py from calling MPI_Finalize()
import mpi4py.rc
mpi4py.rc.finalize   = False

import El
from skylark import sketch, elemhelper
from mpi4py import MPI
import numpy as np
import time

# Configuration
m = 20000;
n = 300;
t = 1000;
#sketches = { "JLT" : sketch.JLT, "FJLT" : sketch.FJLT, "CWT" : sketch.CWT }
sketches = { "JLT" : sketch.JLT, "CWT" : sketch.CWT }

# Set up the random regression problem.
A = El.DistMatrix((El.dTag, El.VR, El.STAR))
El.Uniform(A, m, n)
b = El.DistMatrix((El.dTag, El.VR, El.STAR))
El.Uniform(b, m, 1)

# Solve using Elemental
# Elemental currently does not support LS on VR,STAR.
# So we copy.
A1 = El.DistMatrix()
El.Copy(A, A1)
b1 = El.DistMatrix()
El.Copy(b, b1)
x = El.DistMatrix(El.dTag, El.MC, El.MR)
El.Uniform(x, n, 1)
t0 = time.time()
El.LeastSquares(A1, b1, El.NORMAL, x)
telp = time.time() - t0

# Compute residual
r = El.DistMatrix()
El.Copy(b, r)
El.Gemv(El.NORMAL, -1.0, A1, x, 1.0, r)
res = El.Norm(r)
if (MPI.COMM_WORLD.Get_rank() == 0):
  print "Exact solution residual %(res).3f\t\t\ttook %(elp).2e sec" % \
      { "res" : res, "elp": telp }

# Lower-layers are automatically initilalized when you import Skylark,
# It will use system time to generate the seed. However, we can
# reinitialize for so to fix the seed.
sketch.initialize(123834);

#
# Solve the problem using sketching
#
for sname in sketches:
  stype = sketches[sname]

  t0 = time.time()

  # Create transform.
  S = stype(m, t, defouttype="SharedMatrix")

  # Sketch both A and b using the same sketch
  SA = S * A
  Sb = S * b

  # SA and Sb reside on rank zero, so solving the equation is
  # done there.
  if (MPI.COMM_WORLD.Get_rank() == 0):
    # Solve using NumPy
    [x, res, rank, s] = np.linalg.lstsq(SA.Matrix().ToNumPy(), Sb.Matrix().ToNumPy())
  else:
    x = None

  telp = time.time() - t0

  # Distribute the solution so to compute residual in a distributed fashion
  x = MPI.COMM_WORLD.bcast(x, root=0)

  # Convert x to a distributed matrix.
  # Here we give the type explictly, but the value used is the default.
  x = elemhelper.local2distributed(x, type=El.DistMatrix)

  # Compute residual
  r = El.DistMatrix()
  El.Copy(b, r)
  El.Gemv(El.NORMAL, -1.0, A1, x, 1.0, r)
  res = El.Norm(r)
  if (MPI.COMM_WORLD.Get_rank() == 0):
    print "%(name)s:\tSketched solution residual %(val).3f\ttook %(elp).2e sec" %\
        {"name" : sname, "val" : res, "elp" : telp}

  # As with all Python object they will be automatically garbage
  # collected, and the associated memory will be freed.
  # You can also explicitly free them.
  del S     # S = 0 will also free memory.

# Really no need to "close" the lower layers -- it will do it automatically.
# However, if you really want to you can do it.
sketch.finalize()
#!/usr/bin/env python # MPI usage: # mpiexec -np 2 python skylark/examples/example_sketch.py # prevent mpi4py from calling MPI_Finalize() # Configuration #sketches = { "JLT" : sketch.JLT, "FJLT" : sketch.FJLT, "CWT" : sketch.CWT } # Set up the random regression problem. # Solve using Elemental # Elemental currently does not support LS on VR,STAR. # So we copy. # Compute residual # Lower-layers are automatically initilalized when you import Skylark, # It will use system time to generate the seed. However, we can # reinitialize for so to fix the seed. # # Solve the problem using sketching # # Create transform. # Sketch both A and b using the same sketch # SA and Sb reside on rank zero, so solving the equation is # done there. # Solve using NumPy # Distribute the solution so to compute residual in a distributed fashion # Convert x to a distributed matrix. # Here we give the type explictly, but the value used is the default. # Compute residual # As with all Python object they will be automatically garbage # collected, and the associated memory will be freed. # You can also explicitly free them. # S = 0 will also free memory. # Really no need to "close" the lower layers -- it will do it automatically. # However, if you really want to you can do it.