2電子積分(d,f含む)をGPUで高速に計算する(10倍～20倍)という論文とプログラム
http://ow.ly/10vQyk
http://github.com/miaoyipu/quick
Acceleration of High Angular Momentum Electron Repulsion
Integrals and Integral Derivatives on Graphics Processing Units
Yipu Miao and Kenneth M. Merz, Jr.
ABSTRACT:
We present an efficient implementation of ab initio self-
consistent field (SCF) energy and gradient calculations that run on Compute
Unified Device Architecture (CUDA) enabled graphical processing units
(GPUs) using recurrence relations. We first discuss the machine-generated
code that calculates the electron-repulsion integrals (ERIs) for different ERI
types. Next we describe the porting of the SCF gradient calculation to GPUs,
which results in an acceleration of the computation of the first-order derivative
of the ERIs. However, only s, p, and d ERIs and s and p derivatives could be
executed simultaneously on GPUs using the current version of CUDA and
generation of NVidia GPUs using a previously described algorithm [Miao and Merz
J. Chem. Theory Comput.2013,9, 965-976.].
Hence, we developed an algorithm to compute f type ERIs and d type ERI derivatives on GPUs. Our benchmarks shows the
performance GPU enable ERI and ERI derivative computation yielded speedups of 10-18 times relative to traditional CPU
execution. An accuracy analysis using double-precision calculations demonstrates that the overall accuracy is satisfactory for most
applications.
ほんとだとするとすごい。ソースコードも公開されている。
http://ow.ly/10vQyk
http://github.com/miaoyipu/quick
Acceleration of High Angular Momentum Electron Repulsion
Integrals and Integral Derivatives on Graphics Processing Units
Yipu Miao and Kenneth M. Merz, Jr.
ABSTRACT:
We present an efficient implementation of ab initio self-
consistent field (SCF) energy and gradient calculations that run on Compute
Unified Device Architecture (CUDA) enabled graphical processing units
(GPUs) using recurrence relations. We first discuss the machine-generated
code that calculates the electron-repulsion integrals (ERIs) for different ERI
types. Next we describe the porting of the SCF gradient calculation to GPUs,
which results in an acceleration of the computation of the first-order derivative
of the ERIs. However, only s, p, and d ERIs and s and p derivatives could be
executed simultaneously on GPUs using the current version of CUDA and
generation of NVidia GPUs using a previously described algorithm [Miao and Merz
J. Chem. Theory Comput.2013,9, 965-976.].
Hence, we developed an algorithm to compute f type ERIs and d type ERI derivatives on GPUs. Our benchmarks shows the
performance GPU enable ERI and ERI derivative computation yielded speedups of 10-18 times relative to traditional CPU
execution. An accuracy analysis using double-precision calculations demonstrates that the overall accuracy is satisfactory for most
applications.
ほんとだとするとすごい。ソースコードも公開されている。