KNC – 090 PDF

KNC – 090 PDF

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Appendix B shows a program using the offload model on KNC. We can take advantage of AVX by recompiling the application as shown below:. Optimization methods that benefit applications for KNC should also apply to the KNL processor, although some minor changes will probably be required. At the time this document was written, KNL hardware was not yet released.

For help on code generation, from the command prompt type.

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However, since the application is running on a host the KNL processorall environment variables are set for the host kcn the MIC prefix is not needed anymore.

To run an application on the KNL processor, we just launch the application directly in the processor; the micnativeloadex tool is not necessary anymore.

First, source the environment variables as usual: MKL code will be then dispatched automatically. It is assumed that developers are already familiar with KNC. Depending on each application, developers can refer to the following topics which can be useful for their applications.

In the KNL-F processor i. This document highlights these differences. The top 20 basic blocks are always printed kc the output file by default. We need to recompile it without the offload option for the KNL processor: This restriction will be removed in MKL Although SIMD instructions may be called via inline assembly code or compiler intrinsics, they are platform dependent and unlikely to work between different platforms.


Note that building applications for the KNL processor is lightly different than building it for a 009 as mentioned earlier. To run a native KNC application, the micnativeloadex tool can be used. The current SDE version 7. You may refer to the following document for information on different optimization techniques including prefetching data: Therefore, if your application uses KNC intrinsics, you may refer to the above documents to check whether or not those intrinsics are available for KNL.

There are three mode of operations with KNC: Number of Target devices installed: The SDE supports a mix histogram tool, which can generate the instruction mix histogram. For information on how to read the instruction mix histogram report, please refer to this white paper https: For 0900, if you want to run a binary program, called application, on the KNL platform, and output the first 50 instruction forms: We can take advantage of AVX by recompiling the application as shown below: Finally, use the sde to emulate a knl platform: Appendix C shows a MPI sample code that uses intrinsics to mimic multiplication.

This tool detects all dependent libraries, then transfers the native application and all dependent libraries to the coprocessor and finally runs it on the coprocessor. Set the path to the SDE: To use OpenMP pragmas, 09 command line argument —openmp is needed and the header file omp.


Vector output resulting from multiple input1 and input2: We need to recompile it without the offload option for the KNL processor:. Vector output resulting from shuffle data for pattern ‘AAAA’: For example, if you want to run a binary program, called application, on the KNL platform, and output the first 50 instruction forms:. Vector output resulting from shuffle data for pattern ‘ABCD’: Developers can find more information about AVX in the following documents: To use Intel Cilk Plus, the header file cilk.

Appendix A shows a simple program using different types of shuffle and how multiple intrinsics are compiled with AVX Share Tweet Share Send.

For more complete information about compiler optimizations, see our Optimization Notice. As such, there is no need to offload. To use KNL effectively, applications should effectively use VPU instructions on vector data, good locality of reference, and utilizes caches well in its core computations.

Porting Applications from Knights Corner to Knights Landing

With limited support, MKL To install the SDE, developers can download the kit at https: This section provides suggestions for developers who are porting their KNC coprocessor applications to the KNL processor. The below example shows how nkc allocate and align data to byte in memory. Cluster applications also need fabric scaling. However, there are some minor differences compared to KNC: