FIFO depth optimization

hls4ml/backends/vivado/passes/fifo_depth_optimization.py

@@ -0,0 +1,73 @@
+import json
+
+from pyDigitalWaveTools.vcd.parser import VcdParser
+
+import hls4ml
+from hls4ml.model.optimizer.optimizer import ConfigurableOptimizerPass, ModelOptimizerPass
+
+
+class FifoDepthOptimization(ConfigurableOptimizerPass, ModelOptimizerPass):
+    def __init__(self):
+        self.values = []
+
+    def match(self, node):
+        return True
+
+    def _populate_values(self, name, data, depth):
+        self.values.append({'name': name, 'data': [], 'max': 0, 'depth': 0})
+        get_values = lambda x: int(x[1][1:], 2)
+        self.values[-1]['data'] = [get_values(x) for x in data]
+        self.values[-1]['max'] = max(self.values[-1]['data'])
+        self.values[-1]['depth'] = int(depth[0][1][1:], 2)
+
+    def transform(self, model):
+        model.fifo_opt = True
+        # use `large_fifo_depth = 0` to keep the default fifo depth
+        profiling_fifo_depth = getattr(self, 'profiling_fifo_depth', 100000)
+
+        # check axi-stream or io-stream, if not one the 2 exit
+        if not(model.config.get_config_value('IOType') == 'io_stream'):
+            raise Exception('To use this optimization you have to set `IOType` field to `io_stream` in the HLS config')
+
+        # initialize all the fifos to `profiling_fifo_depth` so that they will be automatically implemented in BRAMs and so they will be
+        # profiled
+
+        if profiling_fifo_depth:
+
+            for k, v in model.output_vars.items():
+                if v == model.get_input_variables()[0] or v == model.get_output_variables()[0]:
+                    continue
+                v.pragma = (v.pragma[0], profiling_fifo_depth)
+
+        model.write()
+        model.build(reset=False, csim=True, synth=True, cosim=True, validation=False, export=False, vsynth=False)
+
+        with open(
+                model.config.get_output_dir() + '/' + model.config.get_project_name() + '_prj' + '/solution1/sim/verilog/fifo_opt.vcd') as vcd_file:
+            vcd = VcdParser()
+            vcd.parse(vcd_file)
+            data = vcd.scope.toJson()
+
+        n_elem = len(data['children'][0]['children'][0]['children'])
+        for i in range(n_elem):
+            name = data['children'][0]['children'][0]['children'][i]['name']
+            data_p = data['children'][0]['children'][0]['children'][i]['children'][0]['data']
+            depth = data['children'][0]['children'][0]['children'][i]['children'][1]['data']
+            self._populate_values(name, data_p, depth)
+
+        maxs = [{'name': i['name'], 'max': i['max'], 'depth': i['depth']} for i in self.values]
+
+        with open(model.config.get_output_dir() + '/max_depth.json', 'w') as f:
+            json.dump(maxs, f, indent=4)
+
+        for k, v in model.output_vars.items():
+            filtered_max = [x['max'] for x in maxs if v.cppname in x['name']]
+            if len(filtered_max) == 0:
+                continue
+            if len(filtered_max) > 1:
+                print('WARNING! Check names of FIFOs')
+            v.pragma = (v.pragma[0], filtered_max[0] + 1)
+
+        model.write()
+        print('[hls4ml] - FIFO optimization completed')
+        return False

hls4ml/backends/vivado/vivado_backend.py

@@ -63,11 +63,17 @@ def _register_flows(self):
         writer_flow_requirements = ['optimize', vivado_types_flow, template_flow]
         self._writer_flow = register_flow('write', writer_passes, requires=writer_flow_requirements, backend=self.name)
 
+        fifo_depth_opt_passes = [
+            'vivado:fifo_depth_optimization'
+        ]
+
+        register_flow('fifo_depth_optimization', fifo_depth_opt_passes, requires=['vivado:ip'], backend=self.name)
+
         all_passes = get_backend_passes(self.name)
 
         extras = [
             # Ideally this should be empty
-            opt_pass for opt_pass in all_passes if opt_pass not in initializers + streaming_passes + quantization_passes + optimization_passes + vivado_types + templates + writer_passes
+            opt_pass for opt_pass in all_passes if opt_pass not in initializers + streaming_passes + quantization_passes + optimization_passes + vivado_types + templates + writer_passes + fifo_depth_opt_passes
         ]
 
         if len(extras) > 0:

hls4ml/backends/vivado_accelerator/passes/fifo_depth_optimization.py

@@ -0,0 +1,88 @@
+import json
+
+from pyDigitalWaveTools.vcd.parser import VcdParser
+
+import hls4ml
+from hls4ml.model.optimizer.optimizer import ConfigurableOptimizerPass, ModelOptimizerPass
+
+
+class FifoDepthOptimization(ConfigurableOptimizerPass, ModelOptimizerPass):
+    def __init__(self):
+        self.values = []
+
+    def match(self, node):
+        return True
+
+    def _populate_values(self, name, data, depth):
+        self.values.append({'name': name, 'data': [], 'max': 0, 'depth': 0})
+        get_values = lambda x: int(x[1][1:], 2)
+        self.values[-1]['data'] = [get_values(x) for x in data]
+        self.values[-1]['max'] = max(self.values[-1]['data'])
+        self.values[-1]['depth'] = int(depth[0][1][1:], 2)
+
+    def transform(self, model):
+        model.fifo_opt = True
+        # use `large_fifo_depth = 0` to keep the default fifo depth
+        profiling_fifo_depth = getattr(self, 'profiling_fifo_depth', 100000)
+
+        # check axi-stream or io-stream, if not one the 2 exit
+        if not(model.config.get_config_value('IOType') == 'io_stream' or
+               model.config.get_config_value('AcceleratorConfig')['Interface'] == 'axi_stream' or
+               model.config.get_config_value('AcceleratorConfig')['Interface'] == 'axi_master'):
+            raise Exception('To use this optimization you have to set `IOType` field to `io_stream` in the HLS config '
+                            'or `axi_stream` or `axi_master` in `AcceleratorConfig` interface field')
+
+        # initialize all the fifos to 10000 so that they will be automatically implemented in BRAMs and so they will be
+        # profiled
+
+        if profiling_fifo_depth:
+
+            for k, v in model.output_vars.items():
+                v.pragma = (v.pragma[0], profiling_fifo_depth)
+
+        model.write()
+        model.build(reset=False, csim=True, synth=True, cosim=True, validation=False, export=False, vsynth=False)
+
+        with open(
+                model.config.get_output_dir() + '/' + model.config.get_project_name() + '_prj' + '/solution1/sim/verilog/fifo_opt.vcd') as vcd_file:
+            vcd = VcdParser()
+            vcd.parse(vcd_file)
+            data = vcd.scope.toJson()
+
+        for i in range(1, len(data['children'][0]['children'][0]['children'])):
+            # wrapper fifos
+            self._populate_values(data['children'][0]['children'][0]['children'][i]['name'],
+                                  data['children'][0]['children'][0]['children'][i]['children'][0]['data'],
+                                  data['children'][0]['children'][0]['children'][i]['children'][1]['data'])
+
+        n_elem = len(data['children'][0]['children'][0]['children'][0]['children'])
+        for i in range(n_elem):
+            name   = data['children'][0]['children'][0]['children'][0]['children'][i]['name']
+            data_p = data['children'][0]['children'][0]['children'][0]['children'][i]['children'][0]['data']
+            depth  = data['children'][0]['children'][0]['children'][0]['children'][i]['children'][1]['data']
+            self._populate_values(name, data_p, depth)
+
+        maxs = [{'name': i['name'], 'max': i['max'], 'depth': i['depth']} for i in self.values]
+
+        with open(model.config.get_output_dir() + '/max_depth.json', 'w') as f:
+            json.dump(maxs, f, indent=4)
+
+        for k, v in model.output_vars.items():
+            filtered_max = [x['max'] for x in maxs if v.cppname in x['name']]
+            if len(filtered_max) == 0:
+                continue
+            if len(filtered_max) > 1:
+                print('WARNING! Check names of FIFOs')
+            v.pragma = (v.pragma[0], filtered_max[0] + 1)
+
+        inp = model.get_input_variables()[0]
+        out = model.get_output_variables()[0]
+        for x in maxs:
+            if 'in_local' in x['name']:
+                inp.pragma = (inp.pragma[0], x['max'] + 1)
+            elif 'out_local' in x['name']:
+                out.pragma = (out.pragma[0], x['max'] + 1)
+
+        model.write()
+        print('[hls4ml] - FIFO optimization completed')
+        return False

hls4ml/backends/vivado_accelerator/vivado_accelerator_backend.py

@@ -55,12 +55,20 @@ def create_initial_config(self, board='pynq-z2', part=None, clock_period=5, io_t
         config['AcceleratorConfig']['Precision']['Output'] = output_type  # float, double or ap_fixed<a,b>
         return config
 
+    def get_default_flow(self):
+        return self._default_flow
+
+    def get_writer_flow(self):
+        return self._writer_flow
+
     def _register_flows(self):
-        #TODO expand this to include new accelerator flow
-        parent_flows = get_backend_flows(backend='vivado')
-        for flow_name in parent_flows:
-            flow = get_flow(flow_name)
-            acc_flow = register_flow(flow_name.replace('vivado:', ''), flow.optimizers, requires=flow.requires, backend=self.name)
-            if ':write' in flow_name:
-                self._writer_flow = acc_flow
-        self._default_flow = 'vivadoaccelerator:ip'
+        vivado_writer = ['vivado:write']
+        vivado_accel_writer = ['vivadoaccelerator:write_hls']
+        self._writer_flow = register_flow('write', vivado_accel_writer, requires=vivado_writer, backend=self.name)
+        self._default_flow = 'vivado:ip'
+
+        fifo_depth_opt_passes = [
+            'vivadoaccelerator:fifo_depth_optimization'
+        ]
+
+        register_flow('fifo_depth_optimization', fifo_depth_opt_passes, requires=['vivado:ip'], backend=self.name)

hls4ml/converters/__init__.py

@@ -143,6 +143,9 @@ def _check_hls_config(config, hls_config):
     if 'LayerType' in hls_config:
         config['HLSConfig']['LayerType'] = hls_config['LayerType']
 
+    if 'Flows' in hls_config:
+        config['HLSConfig']['Flows'] = hls_config['Flows']
+
     if 'Optimizers' in hls_config:
         config['HLSConfig']['Optimizers'] = hls_config['Optimizers']
 

hls4ml/report/vivado_report.py

@@ -30,17 +30,22 @@ def read_vivado_report(hls_dir, full_report=False):
         print('Reports for solution "{}":\n'.format(sln))
         _find_reports(sln_dir + '/' + sln, top_func_name, full_report)
 
-def _parse_build_script(script_path):
+def _parse_build_script(path):
     prj_dir = None
     top_func_name = None
 
-    with open(script_path, 'r') as f:
+    build_path = path + '/build_prj.tcl'
+    project_path = path + '/project.tcl'
+    with open(build_path, 'r') as f:
         for line in f.readlines():
-            if 'open_project' in line:
-                prj_dir = line.split()[-1]
-            elif 'set_top' in line:
+            if 'set_top' in line:
                 top_func_name = line.split()[-1]
 
+    with open(project_path, 'r') as f:
+        for line in f.readlines():
+            if 'set myproject' in line:
+                prj_dir = line.split('"')[-2] + '_prj'
+
     return prj_dir, top_func_name
 
 def _find_solutions(sln_dir):
@@ -105,7 +110,7 @@ def parse_vivado_report(hls_dir):
     top_func_name = None
 
     if os.path.isfile(hls_dir + '/build_prj.tcl'):
-        prj_dir, top_func_name = _parse_build_script(hls_dir + '/build_prj.tcl')
+        prj_dir, top_func_name = _parse_build_script(hls_dir)
 
     if prj_dir is None or top_func_name is None:
         print('Unable to read project data. Exiting.')