Commit f8f879d6 authored by Leonardo Solis's avatar Leonardo Solis
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Update README.md

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README.md

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It achieves speed-ups of up to 2.7x over the original single-threaded AutoDock 4.2 on CPU.



# Development branches



The master branch points to the latest OCLADock-FPGA version: [lga-aoc160](https://git.esa.informatik.tu-darmstadt.de/docking/ocladock-fpga/tree/lga-aoc160).



The other branches are under regular development & optimization. Their labels follow this convention: `<ALGORITHM>-<TOOL>`:



* [ga-aoc160](https://git.esa.informatik.tu-darmstadt.de/docking/ocladock-fpga/tree/ga-aoc160): Genetic Algorithm (traditional) - Altera OpenCL Compiler v16.0

* [lga-intel171](https://git.esa.informatik.tu-darmstadt.de/docking/ocladock-fpga/tree/lga-intel171): Lamarckian Genetic Algorithm - Intel FPGA SDK for OpenCL v17.1

* [lga-sdx174](https://git.esa.informatik.tu-darmstadt.de/docking/ocladock-fpga/tree/lga-sdx174): Lamarckian Genetic Algorithm - Xilinx SDAccel v2017.4



# Development tools



Intel (Altera) OpenCL Compiler v16.0 (Quartus upgraded and patched: 16.0.0.211).

Specific information of the utilized OpenCL tools can be found in the respective README.md for each development branch.



Initialization scripts automate the tool setup-process:

Initialization scripts automate the tool setup-process. E.g.:



```zsh

% source init_aoc160_gidel.sh
@@ -59,16 +69,6 @@ make hw-prof 
make exe

```



# Development branches



The master branch points to the latest OCLADock-FPGA version: [lga-aoc160](https://git.esa.informatik.tu-darmstadt.de/docking/ocladock-fpga/tree/lga-aoc160).



The other branches are regular development & optimization. Their labels follow this convention: `<ALGORITHM>-<TOOL>`



* [ga-aoc160](https://git.esa.informatik.tu-darmstadt.de/docking/ocladock-fpga/tree/ga-aoc160): Genetic Algorithm (traditional) - Altera OpenCL Compiler v16.0

* [lga-intel171](https://git.esa.informatik.tu-darmstadt.de/docking/ocladock-fpga/tree/lga-intel171): Lamarckian Genetic Algorithm - Intel FPGA SDK for OpenCL v17.1

* [lga-sdx174](https://git.esa.informatik.tu-darmstadt.de/docking/ocladock-fpga/tree/lga-sdx174): Lamarckian Genetic Algorithm - Xilinx SDAccel v2017.4



# Documentation



For more details, go to the [Documentation](doc/readme/home.md).