| # Copyright (C) 2020 Arm Limited or its affiliates. All rights reserved. |
| # |
| # SPDX-License-Identifier: Apache-2.0 |
| # |
| # Licensed under the Apache License, Version 2.0 (the License); you may |
| # not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an AS IS BASIS, WITHOUT |
| # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| |
| |
| # Description: |
| # Holds a container for Ethos-U55/System architecture parameters. |
| |
| from .nn_graph import MemArea, TensorPurpose, NpuBlockType, TensorFormat |
| from .numeric_util import round_up, round_up_divide |
| from collections import namedtuple |
| from configparser import ConfigParser |
| from .supported_operators import SupportedOperators |
| import numpy as np |
| import enum |
| |
| PointXY = namedtuple("PointXY", "x y") |
| PointXYZ = namedtuple("PointXYZ", "x y z") |
| |
| |
| class Block: |
| def __init__(self, w, h, d): |
| self.width = w |
| self.height = h |
| self.depth = d |
| |
| def __eq__(self, other): |
| if self.width == other.width and self.height == other.height and self.depth == other.depth: |
| return True |
| else: |
| return False |
| |
| def __repr__(self): |
| return "<Block: {0},{1},{2}>".format(self.width, self.height, self.depth) |
| |
| @classmethod |
| def from_string(cls, s): |
| w, h, c = (int(v) for v in s.split("x")) |
| return cls(w, h, c) |
| |
| |
| class Rect: |
| def __init__(self, x, y, z, x2, y2, z2): |
| self.x = x |
| self.y = y |
| self.z = z |
| self.x2 = x2 |
| self.y2 = y2 |
| self.z2 = z2 |
| |
| def start(self): |
| return PointXYZ(self.x, self.y, self.z) |
| |
| def end(self): |
| return PointXYZ(self.x2, self.y2, self.z2) |
| |
| def size(self): |
| return Block(self.x2 - self.x + 1, self.y2 - self.y + 1, self.z2 - self.z + 1) |
| |
| def __repr__(self): |
| return "<Rect: ({0},{1},{2}) ({3},{4},{5})>".format(self.x, self.y, self.z, self.x2, self.y2, self.z2) |
| |
| |
| class Kernel: |
| def __init__(self, w, h, sx=1, sy=1, dx=1, dy=1): |
| assert sx > 0 and sy > 0 |
| assert dx > 0 and dy > 0 |
| self.width = w |
| self.height = h |
| self.stride = PointXY(sx, sy) |
| self.dilation = PointXY(dx, dy) |
| |
| |
| class SHRAMElements: |
| IFM8 = 0 |
| IFM16 = 1 |
| IFM8_Elementwise = 2 |
| IFM16_Elementwise = 3 |
| Acc16 = 4 |
| Acc32 = 5 |
| Acc40 = 6 |
| Last = Acc40 |
| BitSizes = np.array([8, 16, 8, 16, 16, 32, 40], np.int32) |
| |
| |
| class SHRAMBlockConfig: |
| def __init__(self, sizes, banks): |
| assert len(banks) == SHRAMElements.Last + 1 |
| self.sizes = sizes |
| self.banks = banks |
| |
| |
| # Area indices must match Ethos-U55 SHRAM layout spec |
| class SharedBufferArea(enum.IntEnum): |
| OFM = 0 |
| Weights = 1 |
| IFM = 2 |
| Accumulators = 3 |
| Size = Accumulators + 1 |
| |
| |
| class ArchitectureFeatures: |
| """This class is a container for various parameters of the Ethos-U55 core |
| and system configuration that can be tuned, either by command line |
| parameters or by the Ethos-U55 architects. The class is often passed |
| around to passes that need to do architecture-dependent actions. |
| |
| Note the difference between ArchitectureFeatures and CompilerOptions |
| - ArchitectureFeatures is for changing the Ethos-U55 and system architecture |
| - CompilerOptions is for changing the behaviour of the compiler |
| |
| """ |
| |
| ArchitectureConfig = namedtuple( |
| "ArchitectureConfig", "macs cores ofm_ublock ifm_ublock shram_banks shram_granules elem_units" |
| ) |
| accelerator_configs = { |
| "ethos-u55-256": ArchitectureConfig(256, 1, Block(2, 2, 8), Block(2, 2, 8), 48, [8, 8, 8, 8, 8, 16, 20], 8), |
| "ethos-u55-128": ArchitectureConfig(128, 1, Block(2, 1, 8), Block(2, 2, 8), 24, [4, 4, 4, 4, 4, 8, 12], 4), |
| "ethos-u55-64": ArchitectureConfig(64, 1, Block(1, 1, 8), Block(1, 1, 8), 16, [2, 2, 2, 2, 4, 4, 8], 2), |
| "ethos-u55-32": ArchitectureConfig(32, 1, Block(1, 1, 4), Block(1, 1, 8), 16, [2, 2, 2, 2, 4, 4, 4], 1), |
| } |
| |
| OFMSplitDepth = 16 |
| |
| def __init__( |
| self, |
| vela_config: ConfigParser, |
| accelerator_config, |
| system_config, |
| permanent_storage, |
| inter_pass_cycle_delay, |
| dram_bandwidth, |
| override_block_config, |
| block_config_limit, |
| global_memory_clock_scale, |
| max_blockdep, |
| ): |
| accelerator_config = accelerator_config.lower() |
| self.vela_config = vela_config |
| self.accelerator_config = accelerator_config |
| if not self.accelerator_config in ArchitectureFeatures.accelerator_configs: |
| raise Exception("Unknown accelerator configuration " + self.accelerator_config) |
| accel_config = ArchitectureFeatures.accelerator_configs[self.accelerator_config] |
| self.config = accel_config |
| |
| self.system_config = system_config |
| |
| is_yoda_system = "yoda-" in self.accelerator_config |
| |
| if is_yoda_system: |
| self.sram_size = 256 * 1024 |
| else: |
| self.sram_size = 200 * 1024 * 1024 |
| |
| self.ncores = accel_config.cores |
| self.ofm_ublock = accel_config.ofm_ublock |
| self.ifm_ublock = accel_config.ifm_ublock |
| self.subkernel_max = Block(8, 8, 65536) |
| self.ofm_block_max = Block(64, 32, 128) |
| self.override_block_config = override_block_config |
| self.block_config_limit = block_config_limit |
| |
| self.global_memory_clock_scale = global_memory_clock_scale |
| if self.global_memory_clock_scale <= 0.0 or self.global_memory_clock_scale > 1.0: |
| raise Exception( |
| "Invalid global_memory_clock_scale = " |
| + str(self.global_memory_clock_scale) |
| + " (must be > 0.0 and <= 1.0)" |
| ) |
| |
| self.max_blockdep = max_blockdep |
| |
| dpu_min_height = accel_config.ofm_ublock.height |
| dpu_min_width = accel_config.ofm_ublock.width |
| dpu_dot_product_width = 8 |
| dpu_min_ofm_channels = accel_config.ofm_ublock.depth |
| |
| self.num_elem_wise_units = accel_config.elem_units |
| self.num_macs_per_cycle = dpu_min_height * dpu_min_width * dpu_dot_product_width * dpu_min_ofm_channels |
| |
| self.memory_clock_scales = np.zeros(MemArea.Size) |
| self.memory_port_widths = np.zeros(MemArea.Size) |
| |
| # Get system configuration |
| self.__read_sys_config() |
| |
| # apply the global memory clock scales to the individual ones from the system config |
| for mem in MemArea.all(): |
| self.memory_clock_scales[mem] *= self.global_memory_clock_scale |
| |
| self.memory_clocks = self.memory_clock_scales * self.npu_clock |
| self.memory_bandwidths_per_cycle = self.memory_port_widths * self.memory_clock_scales / 8 |
| |
| if dram_bandwidth != 0: |
| self.memory_bandwidths_per_cycle[MemArea.Dram] = dram_bandwidth * 1e9 / self.npu_clock |
| |
| self.memory_bandwidths_per_second = self.memory_bandwidths_per_cycle * self.npu_clock |
| |
| # sizes as N x H x W x C. we need to round up to these when allocating storage |
| self.storage_rounding_quantums = { |
| TensorFormat.Unknown: (1, 1, 1, 1), |
| TensorFormat.WeightsCompressed: (1, 1, 1, 1), |
| TensorFormat.NHWC: (1, 1, 1, 1), |
| TensorFormat.NHCWB16: (1, 1, 1, 16), |
| } |
| |
| # brick sizes as N x H x W x C. We have to fetch whole bricks at a time |
| self.brick_sizes = { |
| TensorFormat.Unknown: (1, 1, 1, 1), |
| TensorFormat.WeightsCompressed: (1, 1, 1, 1), |
| TensorFormat.NHWC: (1, 1, 1, 1), |
| TensorFormat.NHCWB16: (1, 1, 1, 16), |
| } |
| |
| self.inter_pass_cycle_delay = inter_pass_cycle_delay |
| |
| self.default_weight_format = TensorFormat.WeightsCompressed |
| self.default_feature_map_format = TensorFormat.NHWC |
| |
| if permanent_storage != MemArea.OffChipFlash: |
| self.permanent_storage_mem_area = permanent_storage |
| |
| self.tensor_storage_mem_area = { |
| # permanent mem_area |
| TensorPurpose.Weights: self.permanent_storage_mem_area, |
| TensorPurpose.FeatureMap: self.feature_map_storage_mem_area, |
| } |
| |
| self.tensor_load_mem_area = dict(self.tensor_storage_mem_area) |
| |
| if self.tensor_storage_mem_area[TensorPurpose.Weights] in (MemArea.OffChipFlash,): |
| self.tensor_load_mem_area[TensorPurpose.Weights] = MemArea.Sram |
| |
| self.min_block_sizes = { |
| NpuBlockType.Default: (dpu_min_height, dpu_min_width), |
| NpuBlockType.VectorProduct: (1, 1), |
| NpuBlockType.ConvolutionMxN: (dpu_min_height, dpu_min_width), |
| NpuBlockType.Pooling: (dpu_min_height, dpu_min_width), |
| NpuBlockType.ConvolutionDepthWise: (dpu_min_height, dpu_min_width), |
| NpuBlockType.ElementWise: (1, 1), |
| } |
| |
| self.sub_kernel_limits = { |
| NpuBlockType.Default: (8, 8), |
| NpuBlockType.VectorProduct: (1, 1), |
| NpuBlockType.ConvolutionMxN: (8, 8), |
| NpuBlockType.Pooling: (8, 8), |
| NpuBlockType.ConvolutionDepthWise: (8, 8), |
| NpuBlockType.ElementWise: (1, 1), |
| } |
| |
| # weights for scheduler search |
| from .npu_performance import make_bandwidth_array |
| |
| self.bandwidth_weights = make_bandwidth_array() |
| self.bandwidth_weights[MemArea.Sram] = 1.0 |
| self.bandwidth_weights[MemArea.Dram] = 10.0 |
| self.bandwidth_weights[MemArea.OnChipFlash] = 2.0 |
| self.bandwidth_weights[MemArea.OffChipFlash] = 20.0 |
| self.cycles_weight = 40 |
| self.max_sram_used_weight = 1000 |
| |
| if is_yoda_system: |
| self.max_sram_used_weight = 0 |
| |
| # Shared Buffer Block allocations |
| self.shram_bank_size = 1024 # bytes |
| self.shram_size_bytes = accel_config.shram_banks * self.shram_bank_size |
| self.shram_reserved_output_banks = 2 |
| self.shram_reserved_weight_banks = 0 |
| self.shram_reserved_unused_banks = 2 if accel_config.shram_banks > 16 else 0 |
| self.shram_total_banks = accel_config.shram_banks - self.shram_reserved_unused_banks |
| self.shram_bank_granules = np.array(accel_config.shram_granules, np.int32) |
| |
| # Build a map of acceptable IFM/OFM block configurations up to the maximum |
| # IFM/OFM block size. |
| ifm_block_max = self.get_ifm_block_size(32, self.ofm_block_max, Kernel(8, 8)) |
| self.block_config_map = dict() |
| self.generate_block_config_map(Block(ifm_block_max.width, ifm_block_max.height, 128)) |
| |
| # Setup supported operators and restriction checkers class |
| self.supported_operators = SupportedOperators() |
| |
| # Calculate block configuration for ALL known IFM operations and |
| # accumulator sizes. Consumers will need to select their preferred |
| # operation and bit-width at read-time. |
| def generate_block_config(self, width, height, depth): |
| # Number of bytes required for any SRAM element for a FM of given dimensions |
| size_bytes = (SHRAMElements.BitSizes * (height * width * depth)) // 8 |
| # Convert byte size (rounded) to size in banks |
| size_banks = round_up_divide(size_bytes, self.shram_bank_size) |
| size_banks *= 2 # Double buffer the IFM/Acc (need twice as many banks) |
| # Round bank requirement to bank granularity |
| required_banks = round_up(size_banks, self.shram_bank_granules) |
| return SHRAMBlockConfig(size_bytes, required_banks) |
| |
| @staticmethod |
| def make_block_config_key(width, height, depth): |
| return (int(height), int(width), int(depth)) |
| |
| def get_block_config(self, width, height, depth): |
| assert depth <= self.ofm_block_max.depth |
| key = ArchitectureFeatures.make_block_config_key(width, height, depth) |
| config = self.block_config_map.get(key, None) |
| return config |
| |
| # Generate a key:value map of possible block configurations, where the |
| # key is compounded from the block dimensions: 0x00HHWWCC |
| def generate_block_config_map(self, block: Block): |
| for h in range(1, block.height + 1): |
| for w in range(1, block.width + 1): |
| # All possible IFM/OFM depth values |
| for c in [4, 8, 12, 16, 24, 32, 40, 48, 56, 64, 72, 80, 88, 96, 104, 112, 120, 128]: |
| key = ArchitectureFeatures.make_block_config_key(w, h, c) |
| self.block_config_map[key] = self.generate_block_config(w, h, c) |
| |
| def calc_ifm_block_depth(self, ifm_depth, ifm_bits): |
| assert ifm_bits == 8 or ifm_bits == 16 |
| assert ifm_depth > 0 |
| ifm_depth = round_up(ifm_depth, self.ifm_ublock.depth) |
| max_block_depth = 32 if ifm_bits == 8 else 16 |
| return min(max_block_depth, ifm_depth) |
| |
| # Calculate the size of the IFM block given a depth, target OFM block and a kernel |
| def get_ifm_block_size( |
| self, ifm_block_depth, ofm_block: Block, kernel: Kernel, subkernel: Block = Block(8, 8, 65536) |
| ): |
| upscaling = 1 |
| # Height |
| ifm_odd_2x_height_enable = 0 |
| dilated_kernel_height = ((kernel.height - 1) * kernel.dilation.y) + 1 |
| ifm_block_height = ( |
| (ofm_block.height - 1) * kernel.stride.y |
| + min(subkernel.height, dilated_kernel_height) |
| + ifm_odd_2x_height_enable |
| ) // upscaling |
| |
| if kernel.stride.y == 1: |
| ifm_block_height = round_up(ifm_block_height, self.ofm_ublock.height) |
| elif kernel.stride.y == 2: |
| if (self.ofm_ublock.height == 2) and (ifm_block_height % 4 == 2): |
| ifm_block_height = ifm_block_height + 2 |
| else: |
| ifm_block_height = round_up(ifm_block_height, self.ofm_ublock.height) |
| else: |
| assert False |
| |
| # Width |
| ifm_odd_2x_width_enable = 0 |
| dilated_kernel_width = ((kernel.width - 1) * kernel.dilation.x) + 1 |
| ifm_block_width = ( |
| (ofm_block.width - 1) * kernel.stride.x |
| + min(subkernel.width, dilated_kernel_width) |
| + ifm_odd_2x_width_enable |
| ) // upscaling |
| |
| if kernel.stride.x == 1: |
| ifm_block_width = round_up(ifm_block_width, self.ofm_ublock.width) |
| elif kernel.stride.x == 2: |
| if (self.ofm_ublock.width == 2) and (ifm_block_width % 4 == 2): |
| ifm_block_width = ifm_block_width + 2 |
| else: |
| ifm_block_width = round_up(ifm_block_width, self.ofm_ublock.width) |
| else: |
| assert False |
| |
| return Block(ifm_block_width, ifm_block_height, ifm_block_depth) |
| |
| @staticmethod |
| def intersects(start_a, end_a, start_b, end_b): |
| start_x = max(start_a[0], start_b[0]) |
| end_x = min(end_a[0], end_b[0]) |
| start_y = max(start_a[1], start_b[1]) |
| end_y = min(end_a[1], end_b[1]) |
| start_z = max(start_a[2], start_b[2]) |
| end_z = min(end_a[2], end_b[2]) |
| return ((end_x - start_x) > 0) and ((end_y - start_y) > 0) and ((end_z - start_z) > 0) |
| |
| # Block job dependency: |
| # Does the VOLUME of IFMs for block job B(0) overlap with VOLUME of OFMs block jobs A(8,9,10) |
| # |
| # A | B |
| # ----------------------+------------------ |
| # .... 3,4,5,6,7,8,9,10 | 0,1,2,3,4,5,6,8 10 < JOB NUMBER |
| # |<------->| dependency offset |
| # |
| MAX_BLOCKDEP = 3 |
| |
| # Get the coordinates of a block offset from either the end (negative) |
| # or the start (zero or positive) of the given 3d area |
| def get_offset_block_coords(self, area: Rect, block: Block, offset): |
| size = area.size() |
| # Dimensions of the region, in blocks |
| width_blocks = round_up_divide(size.width, block.width) |
| height_blocks = round_up_divide(size.height, block.height) |
| depth_blocks = round_up_divide(size.depth, block.depth) |
| total_blocks = width_blocks * height_blocks * depth_blocks |
| if offset < 0: |
| index = total_blocks + offset |
| else: |
| index = offset |
| |
| if index >= total_blocks: |
| return None |
| |
| # Coordinates of the indexed block |
| coord_z = block.depth * (index % depth_blocks) |
| coord_y = block.height * (index // (depth_blocks * width_blocks)) |
| coord_x = block.width * ((index // depth_blocks) % width_blocks) |
| |
| return (coord_x + area.x, coord_y + area.y, coord_z + area.z) |
| |
| def get_first_job_input_volume( |
| self, ifm: Rect, ofm: Rect, ifm_block_depth, ofm_block: Block, kernel: Kernel, padLT, block_offset |
| ): |
| # Get ifm block size (jobs are invisibly decomposed into subkernels) |
| ifm_block = self.get_ifm_block_size(ifm_block_depth, ofm_block, kernel, self.ofm_block_max) |
| ifm_depth_blocks = round_up_divide(ifm.size().depth, ifm_block_depth) |
| |
| # Which OFM block are we calculating |
| ofm_coord = self.get_offset_block_coords(ofm, ofm_block, block_offset // ifm_depth_blocks) |
| if ofm_coord is None: |
| return None |
| |
| # Coordinate of the source IFM block |
| ifm_coord_x = max(0, ofm_coord[0] * kernel.stride.x - padLT[0]) |
| ifm_coord_y = max(0, ofm_coord[1] * kernel.stride.y - padLT[1]) |
| ifm_coord_z = ifm.z + (block_offset % ifm_depth_blocks) * ifm_block.depth |
| |
| # IFM block that will be sampled for the FIRST+block_offset job in the next operator's OFM |
| start_coord = (ifm_coord_x, ifm_coord_y, ifm_coord_z) |
| end_coord = ( |
| start_coord[0] + ifm_block.width, |
| start_coord[1] + ifm_block.height, |
| start_coord[2] + ifm_block.depth, |
| ) |
| |
| return (start_coord, end_coord, 1) # start, end, total jobs |
| |
| def get_prev_job_output_volume( |
| self, ifm: Block, ofm: Rect, ifm_block_depth, ofm_block: Block, kernel: Kernel, block_offset |
| ): |
| assert block_offset >= 0 |
| |
| # Get OFM block's volume coordinates |
| start_coord = self.get_offset_block_coords(ofm, ofm_block, -1 - block_offset) |
| if start_coord is None: |
| return None |
| end_coord = ( |
| start_coord[0] + ofm_block.width, |
| start_coord[1] + ofm_block.height, |
| start_coord[2] + ofm_block.depth, |
| ) |
| |
| # Calculate how many IFM blocks this OFM block requires (i.e how many jobs) |
| ifm_block = self.get_ifm_block_size(ifm_block_depth, ofm_block, kernel, self.ofm_block_max) |
| ifm_depth_blocks = round_up_divide(ifm.size().depth, ifm_block_depth) |
| ifm_depth_blocks = 1 # Overwrite with 1 to force OFM block dependency, not IFM |
| |
| return (start_coord, end_coord, ifm_depth_blocks) # start, end, total jobs for this OFM block |
| |
| def calc_block_dep( |
| self, |
| prev_ifm: Block, |
| prev_ofm: Block, |
| prev_ifm_block_depth, |
| prev_ofm_block: Block, |
| prev_kernel: Kernel, |
| ifm: Block, |
| ofm: Block, |
| ifm_block_depth, |
| ofm_block: Block, |
| kernel: Kernel, |
| padLT, |
| ): |
| |
| blockdep = ArchitectureFeatures.MAX_BLOCKDEP |
| |
| # Iterate over the next BLOCKDEP inputs, checking to see if a sliding window |
| # of IFM area overlaps with any previous OFM block generation. |
| elapsed_jobs = 0 |
| ifm_depth = ifm.size().depth |
| for forward_offset in range(ArchitectureFeatures.MAX_BLOCKDEP): |
| # This is the IFM block we want to sample from |
| in_area = self.get_first_job_input_volume( |
| ifm, ofm, ifm_block_depth, ofm_block, kernel, padLT, forward_offset |
| ) |
| if in_area is None: |
| break |
| |
| # Try several previous-OFM blocks in the past (they still might comprise multiple IFM jobs) |
| outstanding_jobs = 0 |
| for block_offset in range(ArchitectureFeatures.MAX_BLOCKDEP): |
| # This is the OFM block being generated by the previous op |
| out_area = self.get_prev_job_output_volume( |
| prev_ifm, prev_ofm, prev_ifm_block_depth, prev_ofm_block, prev_kernel, block_offset |
| ) |
| if out_area is None: |
| break |
| |
| # Block dependency is the max number of allowed outstanding jobs |
| # in the pipeline. Selected by determining how many jobs occur |
| # in between two operators' overlapping OFM->IFM block volumes |
| if ArchitectureFeatures.intersects(in_area[0], in_area[1], out_area[0], out_area[1]): |
| break |
| # Early exit if no intersections and we've seen enough jobs in the pipeline |
| elif outstanding_jobs > ArchitectureFeatures.MAX_BLOCKDEP: |
| break |
| |
| # This OFM had this many jobs (accumulate over multiple OFM blocks) |
| outstanding_jobs += out_area[2] |
| |
| blockdep = min(blockdep, elapsed_jobs + outstanding_jobs) |
| elapsed_jobs += in_area[2] |
| # Early exit if no intersections and we've seen enough jobs in the pipeline |
| if elapsed_jobs > ArchitectureFeatures.MAX_BLOCKDEP: |
| break |
| |
| return blockdep |
| |
| def cpu_cycle_estimate(self, op): |
| """ |
| Gets estimated performance of a CPU operation, based on a linear model of intercept, slope, |
| specified in the vela config file, in ConfigParser file format (.ini file). |
| Example configuration snippet: |
| [CpuPerformance.MyOperationType] |
| Cortex-Mx.intercept=<some float value> |
| Cortex-Mx.slope=<some float value> |
| """ |
| section = "CpuPerformance." + op.type |
| if self.vela_config is not None and section in self.vela_config: |
| op_config = self.vela_config[section] |
| try: |
| intercept = float(op_config.get(self.cpu_config + ".intercept", op_config["default.intercept"])) |
| slope = float(op_config.get(self.cpu_config + ".slope", op_config["default.slope"])) |
| n_elements = op.inputs[0].elements() |
| cycles = intercept + n_elements * slope |
| return cycles |
| except: |
| print("Error: Reading CPU cycle estimate in vela configuration file, section {}".format(section)) |
| raise |
| |
| print("Warning: No configured CPU performance estimate for", op.type) |
| return 0 |
| |
| def __read_sys_config(self): |
| """ |
| Gets the system configuration with the given name from the vela configuration file |
| Example configuration snippet: |
| [SysConfig.MyConfigName] |
| npu_freq=<some float value> |
| cpu=Cortex-Mx |
| ... |
| """ |
| # Get system configuration from the vela configuration file |
| if self.vela_config is None: |
| print("Warning: Using default values for system configuration") |
| else: |
| section_key = "SysConfig." + self.system_config |
| if not section_key in self.vela_config: |
| raise Exception("Unknown system configuration " + self.system_config) |
| |
| try: |
| self.npu_clock = float(self.__sys_config("npu_freq", "500e6")) |
| self.cpu_config = self.__sys_config("cpu", "Cortex-M7") |
| |
| self.memory_clock_scales[MemArea.Sram] = float(self.__sys_config("Sram_clock_scale", "1")) |
| self.memory_port_widths[MemArea.Sram] = int(self.__sys_config("Sram_port_width", "64")) |
| |
| self.memory_clock_scales[MemArea.OnChipFlash] = float(self.__sys_config("OnChipFlash_clock_scale", "1")) |
| self.memory_port_widths[MemArea.OnChipFlash] = int(self.__sys_config("OnChipFlash_port_width", "64")) |
| |
| self.memory_clock_scales[MemArea.OffChipFlash] = float( |
| self.__sys_config("OffChipFlash_clock_scale", "0.25") |
| ) |
| self.memory_port_widths[MemArea.OffChipFlash] = int(self.__sys_config("OffChipFlash_port_width", "32")) |
| |
| self.memory_clock_scales[MemArea.Dram] = float(self.__sys_config("Dram_clock_scale", "1")) |
| self.memory_port_widths[MemArea.Dram] = int(self.__sys_config("Dram_port_width", "32")) |
| |
| self.fast_storage_mem_area = MemArea[self.__sys_config("fast_storage_mem_area", "Sram")] |
| self.feature_map_storage_mem_area = MemArea[self.__sys_config("feature_map_storage_mem_area", "Sram")] |
| self.permanent_storage_mem_area = MemArea[self.__sys_config("permanent_storage_mem_area", "OffChipFlash")] |
| if self.permanent_storage_mem_area not in set((MemArea.OnChipFlash, MemArea.OffChipFlash)): |
| raise Exception( |
| "Invalid permanent_storage_mem_area = " |
| + str(self.permanent_storage_mem_area) |
| + " (must be 'OnChipFlash' or 'OffChipFlash'). To store the weights and other constant data in SRAM" |
| " select 'OnChipFlash'" |
| ) |
| except: |
| print("Error: Reading System Configuration in vela configuration file, section {}".format(section_key)) |
| raise |
| |
| def __sys_config(self, key, default_value): |
| """ |
| Gets the system configuration value with the given key from the vela config file. |
| """ |
| if self.vela_config is None: |
| return default_value |
| section = "SysConfig." + self.system_config |
| result = self.vela_config[section].get(key, None) |
| if result is None: |
| raise Exception("Error: System Configuration Missing key {} in section [{}] ".format(key, section)) |
| return result |