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:warning: **IMPORTANT**: The previous steps do not require an AWS EC2 F1 instance. They can be executed on other AWS EC2 instances such as C4 or C5. However, the steps that follow must be performed on an AWS EC2 F1 instance. You will receive error messages if you do not perform the following steps on an F1 instance.
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1. Execute the following commands in the instance terminal:
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# Practice and Experiment with C/OpenCL Kernels
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# Practice and Experiment with C/C++ and OpenCL Kernels
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Apply and practice what you've learned in the earlier steps of this guide by running more hands-on examples. Familiarize yourself with online resources relating to the SDAccel™ environment, and make your way to the [AWS forum](https://forums.aws.amazon.com/forum.jspa?forumID=243) to search for knowledge and find answers.
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## Run the On-demand SDAccel AWS F1 Developer Labs
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By going through these labs you will learn how to develop accelerated applications using the Xilinx SDAccel development environment.
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[**START THE LABS**](https://github.com/Xilinx/SDAccel-AWS-F1-Developer-Labs)
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<br>
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## Experiment with Other Examples
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Running and experimenting with these three examples of the C/OpenCL™ kernels allows you to further familiarize yourself with good coding practices and kernel optimization techniques.
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### Loop Pipelining
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This example demonstrates how loop pipelining can be used to improve the performance of a kernel.
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Download and run [this example](https://github.com/Xilinx/SDAccel_Examples/tree/2018.2/getting_started/kernel_opt/loop_pipeline_ocl) from the SDAccel GitHub repository.
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Download and run [this example](https://github.com/Xilinx/SDAccel_Examples/tree/master/getting_started/kernel_opt/loop_pipeline_c) from the SDAccel GitHub repository.
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### Reordering Loops
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This example demonstrates how loop reordering can be used to improve the performance of a kernel.
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Download and run [this example](https://github.com/Xilinx/SDAccel_Examples/tree/2018.2/getting_started/kernel_opt/loop_reorder_c) from the SDAccel GitHub repository.
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Download and run [this example](https://github.com/Xilinx/SDAccel_Examples/tree/master/getting_started/kernel_opt/loop_reorder_c) from the SDAccel GitHub repository.
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### Loop Fusion
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This example demonstrates how to fuse two loops into one to improve the performance of an OpenCL kernel.
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Download and run [this example](https://github.com/Xilinx/SDAccel_Examples/tree/2018.2/getting_started/kernel_opt/loop_fusion_c) from the SDAccel GitHub repository.
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Download and run [this example](https://github.com/Xilinx/SDAccel_Examples/tree/master/getting_started/kernel_opt/loop_fusion_c) from the SDAccel GitHub repository.
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### Additional Examples
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The Xilinx Github repository contains more than 80 examples to help you learn. Browse the repository to find more examples of interest, starting with more coding and optimization examples.
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Browse other [OpenCL kernel coding and optimization examples](https://github.com/Xilinx/SDAccel_Examples/tree/2018.2/getting_started/kernel_opt).
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Browse other [C/C++ and OpenCL kernel coding and optimization examples](https://github.com/Xilinx/SDAccel_Examples/tree/master/getting_started/kernel_opt).
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<br>
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<br>
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## Learn More about the SDAccel Environment
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#### SDAccel QuickTake Video Tutorials
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[Fundamental Concepts of Application Host Code](https://www.xilinx.com/video/hardware/concepts-of-application-host-code.html)
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#### Documentation for SDAccel v2018.3
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*_SDx Development Environment Release Notes, Installation, and Licensing Guide_ ([UG1238](https://www.xilinx.com/cgi-bin/docs/rdoc?v=replace;d=ug1238-sdx-rnil.pdf))
*_SDx Development Environment Release Notes, Installation, and Licensing Guide_ ([UG1238](https://www.xilinx.com/html_docs/xilinx2019_1/sdaccel_doc/gsv1547661552998.html#gsv1547661552998))
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## Requirements
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The supported operating systems for SDaccel on-premise development are:
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- Red Hat Enterprise Workstation/Server 7.3-7.4 (64-bit)
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- CentOS 7.2
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- CentOS 7.3-7.4 (64-bit)
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- Ubuntu Linux 16.04.3 LTS (64-bit)
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- Linux kernel 4.4.0 is supported
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- Ubuntu LTS enablement (also called HWE or Hardware Enablement) is _not_ supported
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- Ubuntu 16.04.5 LTS, 18.04.1 LTS
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- CentOS 7.4, 7.5, 7.6
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- RHEL 7.4, 7.5, 7.6
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Visit [this page](https://www.xilinx.com/html_docs/xilinx2019_1/sdaccel_doc/igz1531201833632.html#olw1504034315783) for a complete description of other system requirements.
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# 1. Installing and licensing SDAccel in your own environment
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## Downloading the SDAccel Development Environment
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In order to develop any SDAccel application on-premise, you must install the same version of SDAccel as deployed on AWS F1.
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The SDAccel installer can be found here:
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* Xilinx Vivado v2018.2 or v2018.2.op (64-bit)
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* License: EF-VIVADO-SDX-VU9P-OP
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* SW Build 2258646 on Thu Jun 14 20:02:38 MDT 2018
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* IP Build 2256618 on Thu Jun 14 22:10:49 MDT 2018
In order to develop any SDAccel application on-premise, you must install the same version of SDAccel as deployed on AWS F1. Refer to this page for tool version and download instructions: [enabling development on premises](https://github.com/aws/aws-fpga/edit/master/hdk/docs/on_premise_licensing_help.md)
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## Requesting a License
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If you are a new user, you will also need to obtain an on-premise license of Vivado®. You can request both _node-locked_ and _floating licenses_[here](https://www.xilinx.com/products/design-tools/acceleration-zone/ef-vivado-sdx-vu9p-op-fl-nl.html) (links are on the right side of the page).
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## Installing SDAccel
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* To install the tool, refer to the instructions in the _SDAccel Environment Release Notes, Installation, and Licensing Guide_[(UG1238)](https://www.xilinx.com/support/documentation/sw_manuals/xilinx2018_3/ug1238-sdx-rnil.pdf).
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* To install the tool, refer to the instructions in the _SDAccel Environment Release Notes, Installation, and Licensing Guide_[(UG1238)](https://www.xilinx.com/html_docs/xilinx2019_1/sdaccel_doc/yrc1534452173645.html).
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## Cloning the AWS-FPGA Git Repository
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Execute the following commands to run the SW Emulation step for the SDAccel `helloworld` example:
:warning: **IMPORTANT**: The previous steps do not require an AWS EC2 F1 instance. They can be executed on other AWS EC2 instances such as C4 or C5. However, the steps that follow must be performed on an AWS EC2 F1 instance. You will receive error messages if you do not perform the following steps on an F1 instance.
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1. Execute the following commands in the instance terminal:
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