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Benchmarks

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(Hybrid density functional calculation on the C240 Buckyball)
(Performance tests of the GPU implementation of non-iterative part of the CCSD(T) approach)
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(C22H14, 378 basis set functions, C1 symmetry; 98 nodes: 8 cores per node + 1GPU)
(C22H14, 378 basis set functions, C1 symmetry; 98 nodes: 8 cores per node + 1GPU)
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'''Using 8 CPU cores'''
  Using CUDA CCSD(T) code  
  Using CUDA CCSD(T) code  
  Using 0 device(s) per node  
  Using 0 device(s) per node  
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  Cpu & wall time / sec 9229.9 9240.3  
  Cpu & wall time / sec 9229.9 9240.3  
-
 
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'''Using 7 CPU cores and one GPU'''
  Using CUDA CCSD(T) code  
  Using CUDA CCSD(T) code  
  Using 1 device(s) per node   
  Using 1 device(s) per node   
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  CCSD(T) total energy / hartree = -844.400399501854963  
  CCSD(T) total energy / hartree = -844.400399501854963  
  Cpu & wall time / sec 1468.0 1630.7  
  Cpu & wall time / sec 1468.0 1630.7  
 +
 +
'''Using 1 CPU core and one GPU'''
 +
Using CUDA CCSD(T) code
 +
Using  1 device(s) per node
 +
CCSD[T]  correction energy / hartree =        -0.150973754993069
 +
CCSD[T] correlation energy / hartree =        -3.067917061063028
 +
CCSD[T] total energy / hartree      =      -844.403376796447560
 +
CCSD(T)  correction energy / hartree =        -0.147996460406749
 +
CCSD(T) correlation energy / hartree =        -3.064939766476708
 +
CCSD(T) total energy / hartree      =      -844.400399501861216
 +
Cpu & wall time / sec        1410.9        1756.5

Revision as of 11:37, 11 June 2014


Contents

Benchmarks performed with NWChem

This page contains a suite of benchmarks performed with NWChem. The benchmarks include a variety of computational chemistry methods on a variety of high performance computing platforms. The list of benchmarks available will evolve continuously as new data becomes available. If you have benchmark information you would like to add for your computing system, please contact one of the developers.

Hybrid density functional calculation on the C240 Buckyball

Performance of the Gaussian basis set DFT module in NWChem. This calculation involved performing a PBE0 calculation (in direct mode) on the on C240 system with the 6-31G* basis set (3600 basis functions) without symmetry. These calculations were performed on the Cascade supercomputer located at PNNL. The input file is available.

C240 web4.png

Parallel performance of Ab initio Molecular Dynamics using plane waves

AIMD Parallel timings for UO_2^{2+}+122H2O. These calculations were performed on the Franklin Cray-XT4 computer system at NERSC.
AIMD and AIMD/MM Parallel Timings for Zn2 + +64H2O (unit cell parameters SC=12.4 Angs. and cutoff energy =100Ry). These calculations were performed on the Chinook HP computer system at MSCF EMSL, PNNL.
Exact exchange timings – 80 atom cell of hematite (cutoff energy=100Ry). These calculations were performed on the Franklin Cray-XT4 computer system at NERSC.
Exact exchange timings – 576 atom cell of water (cutoff energy=100Ry). These calculations were performed on the Hopper Cray-XE6 computer system at NERSC.

Parallel performance of the CR-EOMCCSD(T) method (triples part)

An example of the scalability of the triples part of the CR-EOMCCSD(T) approach for Green Fluorescent Protein Chromophore (GFPC) described by cc-pVTZ basis set (648 basis functions) as obtained from NWChem. Timings were determined from calculations on the Franklin Cray-XT4 computer system at NERSC. See the input file for details.

Creomccsd t.png


And more recent scalability test of the CR-EOMCCSD(T) formalism (Jaguar Cray XT5 at ORNL, see K. Kowalski, S. Krishnamoorthy, R.M. Olson, V. Tipparaju, E. Apra, SC2011, for details).

Curve bg lumo.png

Parallel performance of the multireference coupled cluster (MRCC) methods

In collaboration with Dr. Jiri Pittner's group from Heyrovsky Institute of Physical Chemistry implementations of two variants of state-specific MRCC approaches have been developed. During his internship at PNNL Jirka Brabec, using novel processor-group-based algorithms, implemented Brillouin-Wigner and Mukherjee MRCC models with singles and doubles. The scalabililty tests for the Brillouin-Wigner MRCCSD approach have been performed on Jaguar XT5 system at ORNL for β-carotene in 6-31 basis set (472 orbitals, 216 correlated electrons, 20 reference functions; see J.Brabec, J. Pittner, H.J.J. van Dam, E. Apra, K. Kowalski, JCTC 2012, 8(2), pp 487–497). Currently, PNNL postdoctoral fellow Dr. Kiran Bhaskaran Nair is developing perturbative MRCCSD(T) approaches, which accounts for the effect of triple excitations.

Mrccsd scalability.png


Scaling of the triples part of the BW-MRCCSD(T) method for β-carotene in 6-31 basis set (JCP 137, 094112 (2012)). The scalability tests of the BW-MRCCSD(T) implementation of NWChem have been performed on the Jaguar Cray-XK6 computer system of the National Center for Computational Sciences at Oak Ridge National Laboratory.

Mrccsd t titan.png

Timings of CCSD/EOMCCSD for the oligoporphyrin dimer

CCSD/EOMCCSD timings for oligoporphyrin dimer (942 basis functions, 270 correlated electrons, D2h symmetry, excited-state calculations were performed for state of b1g symmetry, in all test calculation convergence threshold was relaxed, 1024 cores were used). See the input file for details.

--------------------------------------------------------
 Iter          Residuum       Correlation     Cpu    Wall
 --------------------------------------------------------
   1   0.7187071521175  -7.9406033677717   640.9   807.7
   ......
 MICROCYCLE DIIS UPDATE: 10 5
  11   0.0009737920958  -7.9953441809574   691.1   822.2
 --------------------------------------------------------
 Iterations converged
 CCSD correlation energy / hartree =        -7.995344180957357
 CCSD total energy / hartree       =     -2418.570838364838890

 EOM-CCSD right-hand side iterations
 --------------------------------------------------------------
      Residuum       Omega / hartree  Omega / eV    Cpu    Wall
 --------------------------------------------------------------
......
Iteration   2 using    6 trial vectors
  0.1584284659595   0.0882389635508    2.40111   865.3  1041.2
Iteration   3 using    7 trial vectors
  0.0575982107592   0.0810948687618    2.20670   918.0  1042.2


Performance tests of the GPU implementation of non-iterative part of the CCSD(T) approach

Recent tests of the GPU CCSD(T) implementation performed on Titan Cray XK7 system at ORNL (C22H14, 378 basis set functions, C1 symmetry; 98 nodes: 8 cores per node + 1GPU)

Using 8 CPU cores

Using CUDA CCSD(T) code 
Using 0 device(s) per node 
CCSD[T] correction energy / hartree = -0.150973754992986 
CCSD[T] correlation energy / hartree = -3.067917061062492 
CCSD[T] total energy / hartree = -844.403376796441080 
CCSD(T) correction energy / hartree = -0.147996460406684 
CCSD(T) correlation energy / hartree = -3.064939766476190 
CCSD(T) total energy / hartree = -844.400399501854849 
Cpu & wall time / sec 9229.9 9240.3 

Using 7 CPU cores and one GPU

Using CUDA CCSD(T) code 
Using 1 device(s) per node  
CCSD[T] correction energy / hartree = -0.150973754993019 
CCSD[T] correlation energy / hartree = -3.067917061062597 
CCSD[T] total energy / hartree = -844.403376796441307 
CCSD(T) correction energy / hartree = -0.147996460406693 
CCSD(T) correlation energy / hartree = -3.064939766476270 
CCSD(T) total energy / hartree = -844.400399501854963 
Cpu & wall time / sec 1468.0 1630.7 

Using 1 CPU core and one GPU

Using CUDA CCSD(T) code
Using   1 device(s) per node
CCSD[T]  correction energy / hartree =        -0.150973754993069
CCSD[T] correlation energy / hartree =        -3.067917061063028
CCSD[T] total energy / hartree       =      -844.403376796447560
CCSD(T)  correction energy / hartree =        -0.147996460406749
CCSD(T) correlation energy / hartree =        -3.064939766476708
CCSD(T) total energy / hartree       =      -844.400399501861216
Cpu & wall time / sec         1410.9         1756.5


Without GPU 9240.3 sec. With GPU 1630.7 sec.

Next release: GPU implementation of non-iterative part of the MRCCSD(T) approach (K. Bhaskarsan-Nair, W. Ma, S. Krishnamoorthy, O. Villa, H. van Dam, E. Apra, K. Kowalski, J. Chem. Theory Comput. 9, 1949 (2013))

GPU MRCCSD T.png

Current developments for high accuracy: alternative task schedulers (ATS)

Currently various development efforts are underway for high accuracy methods that will be available in future releases of NWChem. The examples below shows the first results of the performance of the triples part of Reg-CCSD(T) on GPGPUs (left two examples) and of using alternative task schedules for the iterative CCSD and EOMCCSD.


Other tests:

The impact of the tilesize on the CCSD(ATS) timings: All tests have been performed for uracil trimer (6-31G* basis set; all core electrons frozen) on Hopper using 25 nodes (600 cores). One can observe almost 10-fold speedup of the CCSD(ATS) code for tilesize=40 compared to standard TCE CCSD implementation using tilesize=12.

Uracil trimer.png


Performance tests for water clusters

CTF.png



Luciferin (aug-cc-pVDZ basis set; RHF reference; frozen core) - time per CCSD iteration ( input file)

 tilesize = 30 
   256 cores      644 sec.
   512            378 sec.
   664            314 sec.
  1020            278 sec.
  1300            237 sec.
 tilesize = 40
    128             998 sec.
    256             575 sec.


Sucrose (6-311G** basis set; RHF reference; frozen core) - time per CCSD iteration ( input file)

tilesize = 40
   256 cores   1486 sec. 
   512          910 sec.
  1024          608 sec.


Cytosine-OH (POL1; UHF reference; frozen core) - time per EOMCCSD iteration ( input file)

 tilesize = 30
 256 cores    44.5 sec.
 tilesize = 40 
 128 cores    55.6 sec.