Build IPython integration

.gitignore

@@ -16,3 +16,4 @@ distribute*tar.gz
 core
 .coverage
 htmlcov
+.ipynb_checkpoints

examples/fortran/IPython Integration Demo.ipynb

+{
+ "metadata": {
+  "name": "",
+  "signature": "sha256:5882f90e7a77d4dfd6033f1e8d0d1ff65e244204f12c1bfdf9e7c5abe5e4e11a"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+  {
+   "cells": [
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "# Loopy IPython Integration Demo"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "%load_ext loopy.ipython_ext"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 1
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "## Without transform code"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "%%fortran_kernel\n",
+      "\n",
+      "subroutine fill(out, a, n)\n",
+      "  implicit none\n",
+      "\n",
+      "  real*8 a, out(n)\n",
+      "  integer n, i\n",
+      "\n",
+      "  do i = 1, n\n",
+      "    out(i) = a\n",
+      "  end do\n",
+      "end"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 7
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "print(fill)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "---------------------------------------------------------------------------\n",
+        "KERNEL: fill\n",
+        "---------------------------------------------------------------------------\n",
+        "ARGUMENTS:\n",
+        "a: ValueArg, type: float64\n",
+        "n: ValueArg, type: int32\n",
+        "out: GlobalArg, type: float64, shape: (n), dim_tags: (N0:stride:1)\n",
+        "---------------------------------------------------------------------------\n",
+        "DOMAINS:\n",
+        "[n] -> { [i] : i >= 0 and i <= -1 + n }\n",
+        "---------------------------------------------------------------------------\n",
+        "INAME IMPLEMENTATION TAGS:\n",
+        "i: None\n",
+        "---------------------------------------------------------------------------\n",
+        "INSTRUCTIONS:\n",
+        "[i]                                  out[i] <- a   # insn0\n",
+        "---------------------------------------------------------------------------\n"
+       ]
+      }
+     ],
+     "prompt_number": 8
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "## With transform code"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "split_amount = 128"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 2
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "%%tfortran_kernel\n",
+      "\n",
+      "subroutine tr_fill(out, a, n)\n",
+      "  implicit none\n",
+      "\n",
+      "  real*8 a, out(n)\n",
+      "  integer n, i\n",
+      "\n",
+      "  do i = 1, n\n",
+      "    out(i) = a\n",
+      "  end do\n",
+      "end\n",
+      "\n",
+      "!$loopy begin\n",
+      "!\n",
+      "! tr_fill, = lp.parse_fortran(SOURCE)\n",
+      "! tr_fill = lp.split_iname(tr_fill, \"i\", split_amount,\n",
+      "!     outer_tag=\"g.0\", inner_tag=\"l.0\")\n",
+      "! RESULT = [tr_fill]\n",
+      "!\n",
+      "!$loopy end"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 4
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "print(tr_fill)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "---------------------------------------------------------------------------\n",
+        "KERNEL: tr_fill\n",
+        "---------------------------------------------------------------------------\n",
+        "ARGUMENTS:\n",
+        "a: ValueArg, type: float64\n",
+        "n: ValueArg, type: int32\n",
+        "out: GlobalArg, type: float64, shape: (n), dim_tags: (N0:stride:1)\n",
+        "---------------------------------------------------------------------------\n",
+        "DOMAINS:\n",
+        "[n] -> { [i_outer, i_inner] : i_inner >= -128i_outer and i_inner <= -1 + n - 128i_outer and i_inner >= 0 and i_inner <= 127 }\n",
+        "---------------------------------------------------------------------------\n",
+        "INAME IMPLEMENTATION TAGS:\n",
+        "i_inner: l.0\n",
+        "i_outer: g.0\n",
+        "---------------------------------------------------------------------------\n",
+        "INSTRUCTIONS:\n",
+        "[i_inner,i_outer]                    out[i_inner + i_outer*128] <- a   # insn0\n",
+        "---------------------------------------------------------------------------\n"
+       ]
+      }
+     ],
+     "prompt_number": 6
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": []
+    }
+   ],
+   "metadata": {}
+  }
+ ]
+}
\ No newline at end of file

loopy/ipython_ext.py

+from __future__ import division
+
+from IPython.core.magic import (magics_class, Magics, cell_magic)
+
+import loopy as lp
+
+
+@magics_class
+class LoopyMagics(Magics):
+    @cell_magic
+    def fortran_kernel(self, line, cell):
+        result = lp.parse_fortran(cell.encode())
+
+        for knl in result:
+            self.shell.user_ns[knl.name] = knl
+
+    @cell_magic
+    def tfortran_kernel(self, line, cell):
+        result = lp.parse_transformed_fortran(
+                cell.encode(),
+                transform_code_context=self.shell.user_ns)
+
+        for knl in result:
+            self.shell.user_ns[knl.name] = knl
+
+
+def load_ipython_extension(ip):
+    ip.register_magics(LoopyMagics)