# Benchmarks

### From NWChem

(→Performance tests of the GPU implementation of the non-iterative part of CCSD(T) approach) |
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Line 79: | Line 79: | ||

(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) | ||

- | Using CUDA CCSD(T) code | + | Using CUDA CCSD(T) code |

- | Using 0 device(s) per node | + | Using 0 device(s) per node |

- | CCSD[T] correction energy / hartree = -0.150973754992986 | + | CCSD[T] correction energy / hartree = -0.150973754992986 |

- | CCSD[T] correlation energy / hartree = -3.067917061062492 | + | CCSD[T] correlation energy / hartree = -3.067917061062492 |

- | CCSD[T] total energy / hartree = -844.403376796441080 | + | CCSD[T] total energy / hartree = -844.403376796441080 |

- | CCSD(T) correction energy / hartree = -0.147996460406684 | + | CCSD(T) correction energy / hartree = -0.147996460406684 |

- | CCSD(T) correlation energy / hartree = -3.064939766476190 | + | CCSD(T) correlation energy / hartree = -3.064939766476190 |

- | CCSD(T) total energy / hartree = -844.400399501854849 | + | CCSD(T) total energy / hartree = -844.400399501854849 |

- | Cpu & wall time / sec 9229.9 9240.3 | + | Cpu & wall time / sec 9229.9 9240.3 |

- | Using CUDA CCSD(T) code | + | Using CUDA CCSD(T) code |

- | Using 1 device(s) per node | + | Using 1 device(s) per node |

- | CCSD[T] correction energy / hartree = -0.150973754993019 | + | CCSD[T] correction energy / hartree = -0.150973754993019 |

- | CCSD[T] correlation energy / hartree = -3.067917061062597 | + | CCSD[T] correlation energy / hartree = -3.067917061062597 |

- | CCSD[T] total energy / hartree = -844.403376796441307 | + | CCSD[T] total energy / hartree = -844.403376796441307 |

- | CCSD(T) correction energy / hartree = -0.147996460406693 | + | CCSD(T) correction energy / hartree = -0.147996460406693 |

- | CCSD(T) correlation energy / hartree = -3.064939766476270 | + | CCSD(T) correlation energy / hartree = -3.064939766476270 |

- | 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 |

## Revision as of 08:30, 2 October 2013

# 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 C_{240} Buckyball

Performance of the Gaussian basis set DFT module in NWChem. This calculation involved performing a PBE0 calculation (in direct mode) on the on C_{240} system with the 6-31G* basis set (3600 basis functions) without symmetry. These calculations were performed on the Chinook supercomputer located at PNNL. Timings are per step for the various components. The input file is available.

# Parallel performance of *Ab initio* Molecular Dynamics using plane waves

# 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.

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).

# 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.

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.

# 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 the non-iterative part of CCSD(T) approach

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

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 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

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))

# Current developments for high accuracy: alternative task schedulers

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:

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.