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README.md

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@@ -49,7 +49,8 @@ are automatically inferred based on the tree structure at compile time.
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Since only twelve primitive BOps are specified by snakeHDL, it is straightforward to
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create new compiler backends.
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Wanna use this to implement a Python bytecode interpreter on an FPGA and then make [Snakeware 2](https://github.com/joshiemoore/snakeware) without Linux? Let's build the SNAKE PROCESSOR!!!
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We will use snakeHDL to implement the ALU and control logic for the [Snake Processing Unit](https://github.com/joshiemoore/snakehdl/blob/master/examples/snakepu/design.txt), and then combine
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this with the necessary sequential elements (registers, stack, RAM) to make the snakePU a mega-fast Python coprocessor chip.
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## Binary Operations (BOps)
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The following binary operations are specified by the snakeHDL API and must be implemented in hardware (or simulated hardware) by the compiler backends:
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* BIT
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* JOIN
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...and that's it! snakeHDL is based on a RISC-type philosophy.
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...and that's it!
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Check out the [BOp documentation](https://github.com/joshiemoore/snakehdl/blob/master/docs/bops.md) to learn more or look at the [examples](https://github.com/joshiemoore/snakehdl/tree/master/examples) to see BOps in action.
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## Compiler Targets
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* Add more components to component library
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* Add useful examples demonstrating snakeHDL functionality
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* Optimize compiler output (constant folding, gate pruning, etc.)
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* ***MAKE THE snakePU REAL***

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