Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

First principles calculations were performed to investigate the structural, elastic, and electronic properties of IrN2 for various space groups: cubic Fm-3m and Pa-3, hexagonal P3(2)21, tetragonal P4(2)/mnm, orthorhombic Pmmn, Pnnm, and Pnn2, and monoclinic P2(1)/c. Our calculation indicates that the P2(1)/c phase with arsenopyrite-type structure is energetically more stable than the other phases. It is semiconducting (the remaining phases are metallic) and contains diatomic N-N with the bond distance of 1.414 A. These characters are consistent with the experimental facts that IrN2 is in lower symmetry and nonmetallic. Our conclusion is also in agreement with the recent theoretical studies that the most stable phase of IrN2 is monoclinic P2(1)/c. The calculated bulk modulus of 373 GPa is also the highest among the considered space groups. It matches the recent theoretical values of 357 GPa within 4.3% and of 402 GPa within 7.8%, but smaller than the experimental value of 428 GPa by 14.7%. Chemical bonding and potential displacive phase transitions are discussed for IrN2. For IrN3, cubic skutterudite structure (Im-3) was assumed.

Crystal structures and elastic properties of superhard IrN2 and IrN3 from first principles

Production, properties and potential of graphene

Topological design and additive manufacturing of porous metals for bone scaffolds and orthopaedic implants: A review.

On comparing three artificial neural networks for wind speed forecasting

Fine tuning support vector machines for short-term wind speed forecasting

Bayesian adaptive combination of short-term wind speed forecasts from neural network models

Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market–A state-of-the-art review

Comprehensive evaluation of wind speed distribution models: A case study for North Dakota sites

Gong Li

Papers

On comparing three artificial neural networks for wind speed forecasting

Fine tuning support vector machines for short-term wind speed forecasting

Bayesian adaptive combination of short-term wind speed forecasts from neural network models

Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market–A state-of-the-art review

Comprehensive evaluation of wind speed distribution models: A case study for North Dakota sites