diff --git a/GPy/core/sparse_gp_mpi.py b/GPy/core/sparse_gp_mpi.py
index 73a37862..cecbe667 100644
--- a/GPy/core/sparse_gp_mpi.py
+++ b/GPy/core/sparse_gp_mpi.py
@@ -42,10 +42,10 @@ class SparseGP_MPI(SparseGP):
                 assert isinstance(inference_method, VarDTC_minibatch), 'inference_method has to support MPI!'
                         
         super(SparseGP_MPI, self).__init__(X, Y, Z, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer)
-        self.updates = False
-        self.add_parameter(self.X, index=0)
+        self.update_model(False)
+        self.link_parameter(self.X, index=0)
         if variational_prior is not None:
-            self.add_parameter(variational_prior)
+            self.link_parameter(variational_prior)
 #         self.X.fix()
 
         self.mpi_comm = mpi_comm
@@ -58,7 +58,8 @@ class SparseGP_MPI(SparseGP):
             self.Y_local = self.Y[N_start:N_end]
             print 'MPI RANK '+str(self.mpi_comm.rank)+' with the data range '+str(self.N_range)
             mpi_comm.Bcast(self.param_array, root=0)
-        self.updates = True
+        self.update_model(True)
+
 
     def __getstate__(self):
         dc = super(SparseGP_MPI, self).__getstate__()
diff --git a/GPy/inference/latent_function_inference/var_dtc_parallel.py b/GPy/inference/latent_function_inference/var_dtc_parallel.py
index ab4074f4..a7e2a800 100644
--- a/GPy/inference/latent_function_inference/var_dtc_parallel.py
+++ b/GPy/inference/latent_function_inference/var_dtc_parallel.py
@@ -2,7 +2,7 @@
 # Licensed under the BSD 3-clause license (see LICENSE.txt)
 
 from posterior import Posterior
-from ...util.linalg import jitchol, backsub_both_sides, tdot, dtrtrs
+from ...util.linalg import jitchol, backsub_both_sides, tdot, dtrtrs, dtrtri
 from ...util import diag
 from ...core.parameterization.variational import VariationalPosterior
 import numpy as np
@@ -172,7 +172,9 @@ class VarDTC_minibatch(LatentFunctionInference):
         diag.add(Kmm, self.const_jitter)
         r1 = checkFullRank(Kmm,name='Kmm')
         Lm = jitchol(Kmm)
+        LmInv = dtrtri(Lm)
         
+        #LmInvPsi2LmInvT = LmInv.dot(psi2_full).dot(LmInv.T)
         LmInvPsi2LmInvT = backsub_both_sides(Lm,psi2_full,transpose='right')
         Lambda = np.eye(Kmm.shape[0])+LmInvPsi2LmInvT
         r2 = checkFullRank(Lambda,name='Lambda')