Update the graph maker

1 files changed, 34 insertions, 305 deletions

diff --git a/etc/compile-by-zinc/make-graph.py b/etc/compile-by-zinc/make-graph.py
index c029fd3a1..97c64a644 100755
--- a/etc/compile-by-zinc/make-graph.py
+++ b/etc/compile-by-zinc/make-graph.py
@@ -1,19 +1,18 @@
 #!/usr/bin/env python
 from __future__ import with_statement
 from memoize import memoize
-import codecs, re, sys
+import codecs, re, sys, os
+import subprocess
 
 LAMBDA = u'\u03bb'
 
 OP_NAMES = {'*':'MUL', '+':'ADD', '>>':'SHL', '<<':'SHR', '|':'OR', '&':'AND'}
 
-MAX_INSTRUCTION_WINDOW = 1000
-
-INSTRUCTIONS_PER_CYCLE = 4
-
 REGISTERS = tuple(['RAX', 'RBX', 'RCX', 'RDX', 'RSI', 'RDI', 'RBP', 'RSP']
                   + ['r%d' % i for i in range(8, 16)])
 
+MAX_INSTRUCTION_WINDOW = 10000
+
 CORE_DATA = (('ADD_MUL', 2), ('MUL_CORE', 1), ('LEA_BW', 2))
 CORES = tuple(name for name, count in CORE_DATA)
 CORE_COUNT = dict(CORE_DATA)
@@ -48,9 +47,6 @@ MODEL = {
         } for core_name in REGISTERS)
     }
 
-if len(sys.argv) > 1:
-    MAX_INSTRUCTION_WINDOW = int(sys.argv[1])
-
 def get_lines(filename):
     with codecs.open(filename, 'r', encoding='utf8') as f:
         lines = f.read().replace('\r\n', '\n')
@@ -101,303 +97,36 @@ def create_set(name, items):
     ret += '\n'
     return ret
 
-def schedule(data, basepoint):
-    def make_data_dependencies(input_data):
-        input_var_names = get_input_var_names(input_data)
-        dependencies = dict((var, tuple()) for var in input_var_names)
-        for line in input_data['lines']:
-            dependencies[line['out']] = tuple(arg for arg in line['args']
-                                              if arg[0] not in '0123456789')
-        return dependencies
-
-    def make_reverse_data_dependencies(dependencies):
-        reverse_dependencies = {}
-        for k, v in dependencies.items():
-            for arg in v:
-                if arg not in reverse_dependencies.keys(): reverse_dependencies[arg] = []
-                reverse_dependencies[arg].append(k)
-        return reverse_dependencies
-
-    def get_possible_next_statements(remaining_vars, dependencies):
-        return [var for var in remaining_vars
-                if all(arg not in remaining_vars for arg in dependencies[var])]
-
-    def make_initial_core_state():
-        return {'cores':dict((name, [0] * count) for name, count in CORE_DATA),
-                'registers':dict((name, None) for name in REGISTERS)}
-
-#    def freeze_core_state(core_state):
-#        return (tuple(tuple(core_state['cores'][name]) for name in CORES),
-#                tuple(core_state['registers'][name] for name in REGISTERS))
-#    def unfreeze_core_state(core_state):
-#        return {'cores':dict((name, list(cycles_until_free)) for name, cycles_until_free in zip(CORES, core_state[0])),
-#                'registers':dict((name, var) for name, var in zip(REGISTERS, core_state[1]))}
-
-    def get_initial_indices(input_data):
-        #if basepoint == 0:
-        #    return tuple(list(get_input_var_names(input_data)) + list(get_var_names(input_data)))
-        #else:
-        return tuple(get_var_names(input_data))
-
-
-
-#    def make_source(input_data, var):
-#        input_var_names = get_input_var_names(input_data)
-#        if var in input_var_names: return 'LOAD %s' % var
-
-#    def freeze_core_state(vars_ready_at, core_remaining_cycle_count,
-
-
-
-    dependencies = make_data_dependencies(data)
-    reverse_dependencies = make_reverse_data_dependencies(dependencies)
-
-    def make_initial_core_state():
-        vars_remaining_cycles = {}
-        core_remaining_cycle_count = dict([(core_name, [0] * core_count) for core_name, core_count in CORE_DATA]
-                                          + [(core_name, [0]) for core_name in REGISTERS])
-        cur_instructions_in_cycle = 0
-        return vars_remaining_cycles, core_remaining_cycle_count, cur_instructions_in_cycle
-
-    def freeze_gen(v, rec=(lambda x:x)):
-        if isinstance(v, list):
-            return ('list', tuple(map(rec, v)))
-        if isinstance(v, tuple):
-            return ('tuple', tuple(map(rec, v)))
-        elif isinstance(v, dict):
-            return ('dict', tuple(sorted((k, rec(val)) for k, val in v.items())))
-        else:
-            return v
-    def unfreeze_gen(v, rec=(lambda x:x)):
-        if isinstance(v, tuple):
-            ty, v = v
-            if ty == 'list':
-                return list(map(rec, v))
-            elif ty == 'tuple':
-                return tuple(map(rec, v))
-            elif ty == 'dict':
-                return dict((k, rec(val)) for k, val in v)
-            else:
-                print('Freeze error: %s' % repr((ty, v)))
-                assert False
-        else:
-            return v
-    def freeze(v):
-        return freeze_gen(v, freeze)
-    def unfreeze(v):
-        return unfreeze_gen(v, unfreeze)
-
-    @memoize
-    def update_core_state(var, core, core_state):
-        core = unfreeze(core)
-        (vars_remaining_cycles, core_remaining_cycle_count, cur_instructions_in_cycle) = unfreeze(core_state)
-        cost = 0
-        if cur_instructions_in_cycle >= INSTRUCTIONS_PER_CYCLE:
-            cost += 1
-            cur_instructions_in_cycle = 0
-            for c in core_remaining_cycle_count.keys():
-                for i in range(len(core_remaining_cycle_count[c])):
-                    core_remaining_cycle_count[c][i] = max(0, core_remaining_cycle_count[c][i] - 1)
-            vars_remaining_cycles = dict((var, c - 1) for var, c in vars_remaining_cycles.items()
-                                         if c > 1)
-        cycles_passed = max([min(core_remaining_cycle_count[core['core']['name']])] +
-                            [vars_remaining_cycles[v] for v in dependencies[var] if v in vars_remaining_cycles.keys()])
-        if cycles_passed != 0:
-            cost += cycles_passed
-            cur_instructions_in_cycle = 1
-            for c in core_remaining_cycle_count.keys():
-                for i in range(len(core_remaining_cycle_count[c])):
-                    core_remaining_cycle_count[c][i] = max(0, core_remaining_cycle_count[c][i] - cycles_passed)
-            vars_remaining_cycles = dict((var, c - cycles_passed) for var, c in vars_remaining_cycles.items()
-                                         if c > cycles_passed)
-        else:
-            cur_instructions_in_cycle += 1
-        vars_remaining_cycles[var] = core['latency']
-        assert core_remaining_cycle_count[core['core']['name']][0] == 0
-        core_remaining_cycle_count[core['core']['name']][0] = core['core']['latency']
-        core_remaining_cycle_count[core['core']['name']] = sorted(core_remaining_cycle_count[core['core']['name']])
-        return (cost, freeze((vars_remaining_cycles, core_remaining_cycle_count, cur_instructions_in_cycle)))
-
-    @memoize
-    def evaluate_cost_memo(arg):
-        schedule, core_state = unfreeze_gen(arg)
-        schedule = unfreeze(schedule)
-        (vars_remaining_cycles, core_remaining_cycle_count, cur_instructions_in_cycle) = unfreeze(core_state)
-        if len(schedule) == 0: return max([0] + list(vars_remaining_cycles.values()))
-        (var, core), schedule = schedule[0], schedule[1:]
-        cost, core_state = update_core_state(var, freeze(core), core_state)
-        return cost + evaluate_cost_memo(freeze_gen((freeze(schedule), core_state)))
-
-
-    def add_cycle_info(schedule):
-        vars_remaining_cycles = {}
-        core_remaining_cycle_count = dict([(core_name, [0] * core_count) for core_name, core_count in CORE_DATA]
-                                          + [(core_name, [0]) for core_name in REGISTERS])
-        schedule_with_cycle_info = []
-        cur_cycle = 0
-        cur_instructions_in_cycle = 0
-        for var, core in schedule:
-            if cur_instructions_in_cycle >= INSTRUCTIONS_PER_CYCLE:
-                cur_cycle += 1
-                cur_instructions_in_cycle = 0
-                for c in core_remaining_cycle_count.keys():
-                    for i in range(len(core_remaining_cycle_count[c])):
-                        core_remaining_cycle_count[c][i] = max(0, core_remaining_cycle_count[c][i] - 1)
-                vars_remaining_cycles = dict((var, c - 1) for var, c in vars_remaining_cycles.items()
-                                             if c > 1)
-            cycles_passed = max([min(core_remaining_cycle_count[core['core']['name']])] +
-                                [vars_remaining_cycles[v] for v in dependencies[var] if v in vars_remaining_cycles.keys()])
-            if cycles_passed != 0:
-                cur_cycle += cycles_passed
-                cur_instructions_in_cycle = 1
-                for c in core_remaining_cycle_count.keys():
-                    for i in range(len(core_remaining_cycle_count[c])):
-                        core_remaining_cycle_count[c][i] = max(0, core_remaining_cycle_count[c][i] - cycles_passed)
-                vars_remaining_cycles = dict((var, c - cycles_passed) for var, c in vars_remaining_cycles.items()
-                                             if c > cycles_passed)
-            else:
-                cur_instructions_in_cycle += 1
-            vars_remaining_cycles[var] = core['latency']
-            assert core_remaining_cycle_count[core['core']['name']][0] == 0
-            core_remaining_cycle_count[core['core']['name']][0] = core['core']['latency']
-            core_remaining_cycle_count[core['core']['name']] = sorted(core_remaining_cycle_count[core['core']['name']])
-            schedule_with_cycle_info.append((var,
-                                             {'start':cur_cycle, 'finish':cur_cycle + core['core']['latency']},
-                                             core))
-        return schedule_with_cycle_info
-
-    def evaluate_cost(schedule_with_cycle_info):
-        return max(cycles['finish'] for var, cycles, core in reversed(schedule_with_cycle_info))
-
-
-    var_names = get_var_names(data)
-    lines = dict((line['out'], line) for line in data['lines'])
-
-    @memoize
-    def schedule_remaining(remaining_indices, core_state):
-        def make_schedule(var, core):
-            cost, new_core_state = update_core_state(var, freeze(core), core_state)
-            extra_cost, schedule = schedule_remaining(tuple(i for i in remaining_indices if i != var), new_core_state)
-            return cost + extra_cost, ([(var, core)] + schedule)
-        next_statements = get_possible_next_statements(remaining_indices, dependencies)
-        min_cost, min_schedule = None, None
-        for var in next_statements:
-            if var in lines.keys():
-                for core in MODEL[lines[var]['op']]:
-                    cost, schedule = make_schedule(var, core)
-                    if min_cost is None or cost < min_cost:
-                        min_cost, min_schedule = cost, schedule
-#                    return min_cost, min_schedule
-            else:
-                for core in MODEL['LOAD']:
-                    cost, schedule = make_schedule(var, core)
-                    if min_cost is None or cost < min_cost:
-                        min_cost, min_schedule = cost, schedule
-#                    return min_cost, min_schedule
-        if min_cost is None:
-            min_cost, min_schedule = evaluate_cost_memo(freeze_gen((freeze([]), core_state))), []
-        return min_cost, min_schedule
-
-    core_state = freeze(make_initial_core_state())
-    cost, schedule = schedule_remaining(get_initial_indices(data), core_state) #, freeze_core_state(make_initial_core_state()))
-    schedule_with_cycle_info = add_cycle_info(schedule)
-    for var, cycles, core in schedule_with_cycle_info:
-        if var in lines.keys():
-            print('%s; // %s, start: %s, end: %s' % (lines[var]['source'], core['core']['name'], basepoint + cycles['start'], basepoint + cycles['finish']))
-        else:
-            print('LOAD %s; // %s, start: %s, end: %s' % (var, core['core']['name'], basepoint + cycles['start'], basepoint + cycles['finish']))
-    return basepoint + cost
-
-    def make_decls(input_data):
-        var_names = get_var_names(input_data)
-        ret = ''
-        ret += 'include "alldifferent.mzn";\n'
-        ret += 'include "cumulative.mzn";\n'
-        for line in input_data['lines']:
-            ret += '%%%s\n' % line['source']
-        ret += create_set('CORE', CORES)
-        ret += create_set('INSTRUCTIONS', list(var_names))
-        ret += create_set('OPS', list(OP_NAMES.values()))
-        MAX_NUMBER_OF_NOOPS_PER_INSTRUCTION = 3
-        APPROXIMATE_MAX_LATENCY = 6 * INSTRUCTIONS_PER_CYCLE
-        max_loc = len(var_names) * MAX_NUMBER_OF_NOOPS_PER_INSTRUCTION + APPROXIMATE_MAX_LATENCY
-        ret += 'int: MAX_LOC = %d;\n\n' % max_loc
-        ret += 'set of int: LOCATIONS = 1..MAX_LOC;\n'
-        ret += 'array[INSTRUCTIONS] of var LOCATIONS: output_locations;\n'
-        ret += 'array[INSTRUCTIONS] of var int: output_data_latency;\n'
-        ret += 'array[INSTRUCTIONS] of var int: output_core_latency;\n'
-        ret += 'array[INSTRUCTIONS] of var CORE: output_cores;\n'
-        ret += 'array[INSTRUCTIONS] of OPS: input_ops = [%s];\n' % ', '.join(OP_NAMES[line['op']] for line in input_data['lines'])
-        for core in CORES:
-            ret += 'array[INSTRUCTIONS] of var int: output_%s_core_latency;\n' % core
-            ret += 'array[INSTRUCTIONS] of var 0..1: output_%s_core_use;\n' % core
-            ret += 'constraint forall (i in INSTRUCTIONS) (0 <= output_%s_core_latency[i]);\n' % core
-            ret += 'constraint forall (i in INSTRUCTIONS) (output_%s_core_use[i] == 1 -> output_core_latency[i] == output_%s_core_latency[i]);\n' % (core, core)
-        ret += 'var LOCATIONS: RET_loc;\n'
-        ret += '\n'
-        return ret
-
-    def make_cores(input_data):
-        ret = ''
-        for opc, cores in MODEL.items():
-            possible_cores = []
-            for core in cores:
-                conjuncts = (['output_cores[i] == %s' % core['core']['name'],
-                              'output_%s_core_use[i] == 1' % core['core']['name'],
-                              'output_%s_core_latency[i] == %d' % (core['core']['name'], core['core']['latency'] * INSTRUCTIONS_PER_CYCLE),
-                              'output_data_latency[i] == %d' % (core['latency'] * INSTRUCTIONS_PER_CYCLE)] +
-                             ['output_%s_core_use[i] == 0 /\ output_%s_core_latency[i] == 0' % (other_core, other_core)
-                              for other_core in CORES if other_core != core['core']['name']])
-                possible_cores.append('(%s)' % (r' /\ '.join(conjuncts)))
-            ret += ('constraint forall (i in INSTRUCTIONS) (input_ops[i] == %s -> (%s));\n'
-                    % (OP_NAMES[opc], r' \/ '.join(possible_cores)))
-        ret += '\n'
-        for core in CORES:
-            ret += ('constraint cumulative(output_locations, output_%s_core_latency, output_%s_core_use, %d);\n'
-                    % (core, core, CORE_COUNT[core]))
-        return ret
-
-    def make_disjoint(input_data):
-        var_names = get_var_names(input_data)
-        ret = ''
-        ret += 'constraint alldifferent(output_locations);\n'
-        return ret
-
-    def make_dependencies(input_data):
-        var_names = get_var_names(input_data)
-        ret = ''
-        for line in input_data['lines']:
-            for arg in line['args']:
-                if arg in var_names and arg[0] not in '0123456789':
-                    ret += ('constraint output_locations[%s] + output_data_latency[%s] <= output_locations[%s];\n'
-                            % (arg, arg, line['out']))
-        ret += '\n'
-        ret += 'constraint max([ output_locations[i] + output_data_latency[i] | i in INSTRUCTIONS ]) <= RET_loc;\n'
-        ret += '\n'
-        return ret
-
-
-
-    def make_output(input_data):
-        ret = 'solve minimize RET_loc;\n\n'
-        ret += 'output [ "(" ++ show(INSTRUCTIONS_NAMES[i]) ++ ", " ++ show(CORE_NAMES[fix(output_cores[i])]) ++ ", " ++ show(output_locations[i]) ++ ", " ++ show(output_data_latency[i]) ++ ", " ++ show(output_core_latency[i]) ++ ") ,\\n"\n'
-        ret += '       | i in INSTRUCTIONS ];\n'
-        ret += 'output [ "RET_loc: " ++ show(RET_loc) ];\n'
-        return ret
-
-#    return '\n'.join([
-#        make_decls(data),
-#        make_disjoint(data),
-#        make_dependencies(data),
-#        make_cores(data),
-#        make_output(data)
-#        ])
+def make_data_dependencies(input_data):
+    input_var_names = get_input_var_names(input_data)
+    dependencies = dict((var, tuple()) for var in input_var_names)
+    for line in input_data['lines']:
+        dependencies[line['out']] = tuple(arg for arg in line['args']
+                                          if arg[0] not in '0123456789')
+    return dependencies
+
+def make_reverse_data_dependencies(dependencies):
+    reverse_dependencies = {}
+    for k, v in dependencies.items():
+        for arg in v:
+            if arg not in reverse_dependencies.keys(): reverse_dependencies[arg] = []
+            reverse_dependencies[arg].append(k)
+    return reverse_dependencies
+
+def print_dependencies(input_data, dependencies):
+    in_vars = get_input_var_names(input_data)
+    out_vars = get_output_var_names(input_data)
+    return ('digraph G {\n' +
+            ''.join('    %s -> in;\n' % var for var in in_vars) +
+            ''.join('    out -> %s;\n' % var for var in out_vars) +
+            ''.join(''.join('    %s -> %s;\n' % (out_var, in_var) for out_var in sorted(dependencies[in_var]))
+                    for in_var in sorted(dependencies.keys())) +
+            '}\n')
 
 data_list = parse_lines(get_lines('femulDisplay.log'))
-basepoint = 0
 for i, data in enumerate(data_list):
-    basepoint = schedule(data, basepoint)
-    print(basepoint)
-    sys.exit(0)
-
-print(basepoint)
+    deps = print_dependencies(data, make_data_dependencies(data))
+    with codecs.open('femulData%d.dot' % i, 'w', encoding='utf8') as f:
+        f.write(deps)
+    for fmt in ('png', 'svg'):
+        subprocess.call(['dot', '-T%s' % fmt, 'femulData%d.dot' % i, '-o', 'femulData%d.%s' % (i, fmt)])