hiop | HPC solver for nonlinear optimization problems | GPU library

 by   LLNL C++ Version: v0.7.2 License: Non-SPDX

kandi X-RAY | hiop Summary

kandi X-RAY | hiop Summary

hiop is a C++ library typically used in Hardware, GPU applications. hiop has no bugs, it has no vulnerabilities and it has low support. However hiop has a Non-SPDX License. You can download it from GitHub.

HiOp is an optimization solver for solving certain mathematical optimization problems expressed as nonlinear programming problems. HiOp is a lightweight HPC solver that leverages application's existing data parallelism to parallelize the optimization iterations by using specialized linear algebra kernels.
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            kandi-support Support

              hiop has a low active ecosystem.
              It has 176 star(s) with 33 fork(s). There are 16 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 28 open issues and 220 have been closed. On average issues are closed in 149 days. There are 8 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of hiop is v0.7.2

            kandi-Quality Quality

              hiop has 0 bugs and 0 code smells.

            kandi-Security Security

              hiop has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              hiop code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              hiop has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              hiop releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.

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            hiop Key Features

            No Key Features are available at this moment for hiop.

            hiop Examples and Code Snippets

            No Code Snippets are available at this moment for hiop.

            Community Discussions

            QUESTION

            Scroll to specific div/height after loading page if certain condition matches
            Asked 2018-Apr-03 at 06:08

            I want to scroll to a div after loading page means my starting point is that specific div and curser should point to that div.i tried several things ,

            ...

            ANSWER

            Answered 2018-Apr-02 at 13:27

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install hiop

            Enable/disable MPI: -DHIOP_USE_MPI=[ON/OFF] (by default ON)
            GPU support: -DHIOP_USE_GPU=ON. MPI can be either off or on. For more build system options related to GPUs, see "Dependencies" section below.
            Enable/disable "developer mode" build that enforces more restrictive compiler rules and guidelines: -DHIOP_DEVELOPER_MODE=ON. This option is by default off.
            Additional checks and self-diagnostics inside HiOp meant to detect abnormalities and help to detect bugs and/or troubleshoot problematic instances: -DHIOP_DEEPCHECKS=[ON/OFF] (by default ON). Disabling HIOP_DEEPCHECKS usually provides 30-40% execution speedup in HiOp. For full strength, it is recommended to use HIOP_DEEPCHECKS with debug builds. With non-debug builds, in particular the ones that disable the assert macro, HIOP_DEEPCHECKS does not perform all checks and, thus, may overlook potential issues.

            Support

            When GPU support is on, HiOp requires Magma linear solver library and CUDA Toolkit. Both are detected automatically in most cases. The typical cmake command to enable GPU support in HiOp is. When Magma is not detected, one can specify its location by passing -DHIOP_MAGMA_DIR=/path/to/magma/dir to cmake. For custom CUDA Toolkit installations, the locations to the (missing/not found) CUDA libraries can be specified to cmake via -DNAME=/path/cuda/directory/lib, where NAME can be any of.
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