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Description: PGI安装liscence，这个liscence应该是永久的，大家可以试试看-liscence of pgi
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Size: 1024 |
Author: xhm |
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Description: pgina核心源代码，PGINA是Windows的一个开源扩展，允许通过附加的额外代码提供各种类型的认证服务。-pgina core source code, PGINA is an open source Windows extension allows additional code to provide additional types of certification services.
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Size: 77824 |
Author: hq |
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Description: PGI cuda Fortran编程手册-CUDA Fortran Programming Guide and Reference
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Size: 1292288 |
Author: zhutong |
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Description: 用于使用pgi编译器编译并行环境mpich1中环境变量的设置-pgi compile mpich1
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Size: 20175872 |
Author: 何清㟆 |
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Description: piglet解释器，用于运行piglet程序。输入java PgInterpreter < filename即可-piglet interpreter used to run the piglet program. Input java PgInterpreter < filename can
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Size: 59392 |
Author: z |
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Description: pgi7.0 license
pgi7.0 license
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Size: 1024 |
Author: 马梓博 |
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Description: 在linux上安装pgi编译器的全过程，请大家参考，以方便大家自己安装-install pgi
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Size: 1024 |
Author: sunchy |
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Description: 如果PGI过期，可以考虑将license.dat进行替换，然后重新编译 ，目录为opt/pgi下面-if your pgi can,t work you can put this under the path opt/pgi
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Size: 10240 |
Author: sunchy |
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Description: 基于粒子群算法的电力系统负荷分配问题（1）数学模型：
以IEEE 3机6节点为工况模型 ，Load=850MW
（2）目标函数：
minF=∑(i=1，Ng)Fi(PGi)，Fi(PGi) =aiPi2+biPi+ci+Ei，考虑阀点(Valve-Point)效应
（3）约束条件：
a.发电机组输出功率上下限约束，即PGi min<=PGi<= PGimax；
b.电力负荷平衡约束，忽略网损，即∑(i=1，Ng)（PGi）= PGD-Based on particle swarm optimization of power system load allocation problem
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Size: 2048 |
Author: 石娟 |
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Description: 使用PGI编译器用openacc进行GPU并行计算的一些training code ，详见readme文件(Some training code with openacc for GPU parallel computing using the PGI compiler, as detailed in the readme file)
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Size: 380928 |
Author: Dovahkiin
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Description: CUDA Fortran 高效编程实践_科学家和工程师特供
2007 年以来，以 nVidia GPU 为代表的加速器并行计算风起云涌，带有加速器的超级计 算机在 TOP500 中的份额逐年增加，支持加速器的主流应用软件也呈爆炸式增长，研究加速 器计算的技术人员数以百万计，世界范围内的大学、研究机构竞相开设相关课程。
目前流行的 GPU 通用编程语言是 CUDA C 和 OpenCL. 它们均是 C/C++语言的扩展，因 此可以方便地将 C/C++代码移植到 GPU 上。但对于科学与工程计算中的重要编程语言 Fortran，无法直接地改写为 CUDA C 或 OpenCL。很多久经考验的应用程序都是用 Fortran 开发，如果完全改写，工作量巨大，而且有不可估量的稳定性风险。
为使 Fortran 应用能够使用 GPU 加速，The Portland Group 设计了 CUDA Fortran 语言， 并在自家的 PGI 编译器中支持。气象、理论物理等领域的应用经过简单的改造，就能够利 用 GPU 的强大计算能力。(CUDA FORTRAN efficient programming practice
Since 2007, with NVIDIA GPU as the representative of accelerator parallel computing, the share of supercomputers with accelerators in top 500 has increased year by year, and the mainstream application software supporting accelerators has also grown explosively. There are millions of technicians studying accelerator computing, and universities and research institutions around the world are competing to offer relevant courses.
To enable FORTRAN applications to use GPU acceleration, the Portland group designed CUDA FORTRAN language, which is supported in its own PGI compiler. The application of meteorology, theoretical physics and other fields can make use of the powerful computing power of GPU after simple transformation.)
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Size: 2135040 |
Author: zzfthu |
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