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import time
import struct
import numpy as np
from typing import Tuple, List, Dict, Optional, Any
try:
import vulkan as vk
except (ImportError, OSError): # minimal hosts (e.g. HF Space slim image):
vk = None # without the native loader; engine init degrades honestly
from src.paths import resource
class VulkanComputeEngine:
"""
Persistent Vulkan 1.2+ Compute Engine for biological neural connectome simulation.
Features:
- Capability-based device selection (Discrete > Integrated > CPU)
- Persistent device buffer allocations (no per-step reallocations)
- GPU-resident neural state (potentials, binary spikes, refractory counters, weights)
- Persistent descriptor sets and compute pipelines
- Deterministic synchronization via pipeline barriers
- High-resolution dispatch latency & throughput telemetry
"""
def __init__(
self,
gpu_index: Optional[int] = None,
enable_validation: bool = False
):
self.enable_validation = enable_validation
self.gpu_index = gpu_index
self.instance = None
self.physical_device = None
self.device = None
self.queue = None
self.queue_family_idx = None
self.command_pool = None
self.descriptor_pool = None
self.device_name = "Unknown"
self.device_type = 0
self.device_type_str = "Unknown"
self.driver_version = 0
self.device_memory_properties = None
# Pipelines
self.brain_pipeline = None
self.brain_layout = None
self.brain_desc_layout = None
self.plasticity_pipeline = None
self.plasticity_layout = None
self.plasticity_desc_layout = None
# Persistent Circuit State Resources
self.loaded_circuit_hash = None
self.num_neurons = 0
self.num_synapses = 0
self.persistent_buffers = {}
self.brain_descriptor_set = None
self.plasticity_descriptor_set = None
self.brain_command_buffer = None
self.plasticity_command_buffer = None
# Diagnostics
self.last_step_latency_ms = 0.0
self.last_plasticity_latency_ms = 0.0
self.total_steps_executed = 0
if vk is None:
raise RuntimeError("Vulkan bindings unavailable on this host "
"(no native loader); CPU reference is the honest fallback.")
self._init_vulkan()
def _find_memory_type(self, type_filter: int, properties: int) -> int:
for i in range(self.device_memory_properties.memoryTypeCount):
if (type_filter & (1 << i)) and (self.device_memory_properties.memoryTypes[i].propertyFlags & properties) == properties:
return i
raise RuntimeError("Failed to find suitable memory type!")
def _init_vulkan(self):
app_info = vk.VkApplicationInfo(
sType=vk.VK_STRUCTURE_TYPE_APPLICATION_INFO,
pApplicationName="FlyBrainVulkanEngine",
applicationVersion=vk.VK_MAKE_VERSION(1, 1, 0),
pEngineName="FlyBrain",
engineVersion=vk.VK_MAKE_VERSION(1, 1, 0),
apiVersion=vk.VK_MAKE_VERSION(1, 2, 0),
)
layers = []
if self.enable_validation:
layers.append("VK_LAYER_KHRONOS_validation")
create_info = vk.VkInstanceCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_INSTANCE_CREATE_INFO,
pApplicationInfo=app_info,
enabledExtensionCount=0,
ppEnabledExtensionNames=[],
enabledLayerCount=len(layers),
ppEnabledLayerNames=layers,
)
self.instance = vk.vkCreateInstance(create_info, None)
# 1. Capability-based physical device selection
pdevs = vk.vkEnumeratePhysicalDevices(self.instance)
if not pdevs:
raise RuntimeError("No Vulkan physical devices found!")
selected_dev = None
selected_q_fam = None
selected_props = None
# Prioritize: DISCRETE_GPU (2) > INTEGRATED_GPU (1) > CPU (4)
scored_devices = []
for idx, dev in enumerate(pdevs):
props = vk.vkGetPhysicalDeviceProperties(dev)
q_fam_props = vk.vkGetPhysicalDeviceQueueFamilyProperties(dev)
compute_fam = -1
for q_idx, q_fam in enumerate(q_fam_props):
if q_fam.queueFlags & vk.VK_QUEUE_COMPUTE_BIT:
compute_fam = q_idx
break
if compute_fam == -1:
continue
type_score = (
100 if props.deviceType == vk.VK_PHYSICAL_DEVICE_TYPE_DISCRETE_GPU else
50 if props.deviceType == vk.VK_PHYSICAL_DEVICE_TYPE_INTEGRATED_GPU else
10 if props.deviceType == vk.VK_PHYSICAL_DEVICE_TYPE_CPU else 1
)
scored_devices.append((type_score, idx, dev, compute_fam, props))
if not scored_devices:
raise RuntimeError("No compute-capable Vulkan physical devices found!")
scored_devices.sort(key=lambda x: x[0], reverse=True)
if self.gpu_index is not None and 0 <= self.gpu_index < len(pdevs):
# Explicit index selection
for item in scored_devices:
if item[1] == self.gpu_index:
_, _, selected_dev, selected_q_fam, selected_props = item
break
if selected_dev is None:
_, _, selected_dev, selected_q_fam, selected_props = scored_devices[0]
self.physical_device = selected_dev
self.queue_family_idx = selected_q_fam
self.device_name = selected_props.deviceName
self.device_type = selected_props.deviceType
self.device_type_str = (
"Discrete GPU" if selected_props.deviceType == vk.VK_PHYSICAL_DEVICE_TYPE_DISCRETE_GPU else
"Integrated GPU" if selected_props.deviceType == vk.VK_PHYSICAL_DEVICE_TYPE_INTEGRATED_GPU else
"CPU" if selected_props.deviceType == vk.VK_PHYSICAL_DEVICE_TYPE_CPU else "Other"
)
self.driver_version = selected_props.driverVersion
self.device_memory_properties = vk.vkGetPhysicalDeviceMemoryProperties(self.physical_device)
# 2. Logical Device Creation
q_create = vk.VkDeviceQueueCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_DEVICE_QUEUE_CREATE_INFO,
queueFamilyIndex=self.queue_family_idx,
queueCount=1,
pQueuePriorities=[1.0],
)
d_create = vk.VkDeviceCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_DEVICE_CREATE_INFO,
queueCreateInfoCount=1,
pQueueCreateInfos=[q_create],
enabledExtensionCount=0,
ppEnabledExtensionNames=[],
pEnabledFeatures=None,
)
self.device = vk.vkCreateDevice(self.physical_device, d_create, None)
self.queue = vk.vkGetDeviceQueue(self.device, self.queue_family_idx, 0)
# 3. Command Pool
cmd_pool_info = vk.VkCommandPoolCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_COMMAND_POOL_CREATE_INFO,
queueFamilyIndex=self.queue_family_idx,
flags=vk.VK_COMMAND_POOL_CREATE_RESET_COMMAND_BUFFER_BIT,
)
self.command_pool = vk.vkCreateCommandPool(self.device, cmd_pool_info, None)
# 4. Descriptor Pool
pool_sizes = [
vk.VkDescriptorPoolSize(
type=vk.VK_DESCRIPTOR_TYPE_STORAGE_BUFFER,
descriptorCount=2048,
)
]
pool_info = vk.VkDescriptorPoolCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_DESCRIPTOR_POOL_CREATE_INFO,
flags=vk.VK_DESCRIPTOR_POOL_CREATE_FREE_DESCRIPTOR_SET_BIT,
maxSets=256,
poolSizeCount=len(pool_sizes),
pPoolSizes=pool_sizes,
)
self.descriptor_pool = vk.vkCreateDescriptorPool(self.device, pool_info, None)
# 5. Build Compute Pipelines
self._init_brain_pipeline()
self._init_plasticity_pipeline()
def _create_buffer(self, size_bytes: int, usage: int):
buf_info = vk.VkBufferCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_BUFFER_CREATE_INFO,
size=size_bytes,
usage=usage,
sharingMode=vk.VK_SHARING_MODE_EXCLUSIVE,
)
buf = vk.vkCreateBuffer(self.device, buf_info, None)
reqs = vk.vkGetBufferMemoryRequirements(self.device, buf)
mem_type_idx = self._find_memory_type(
reqs.memoryTypeBits,
vk.VK_MEMORY_PROPERTY_HOST_VISIBLE_BIT | vk.VK_MEMORY_PROPERTY_HOST_COHERENT_BIT
)
alloc_info = vk.VkMemoryAllocateInfo(
sType=vk.VK_STRUCTURE_TYPE_MEMORY_ALLOCATE_INFO,
allocationSize=reqs.size,
memoryTypeIndex=mem_type_idx,
)
mem = vk.vkAllocateMemory(self.device, alloc_info, None)
vk.vkBindBufferMemory(self.device, buf, mem, 0)
return buf, mem, reqs.size
def _init_brain_pipeline(self):
spv_path = resource("shaders/brain_step.spv")
if not os.path.exists(spv_path):
raise FileNotFoundError(f"SPIR-V compute shader missing: {spv_path}")
with open(spv_path, "rb") as f:
code = f.read()
mod_info = vk.VkShaderModuleCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_SHADER_MODULE_CREATE_INFO,
codeSize=len(code),
pCode=code,
)
shader_module = vk.vkCreateShaderModule(self.device, mod_info, None)
# 11 bindings for LIF:
# 0: RowOffsets, 1: ColIndices, 2: Weights, 3: PrevSpikes, 4: ExternalInputs,
# 5: PotentialsIn, 6: RefractoryIn, 7: PotentialsOut, 8: SpikesOut, 9: RefractoryOut, 10: Params
bindings = []
for b_idx in range(11):
bindings.append(vk.VkDescriptorSetLayoutBinding(
binding=b_idx,
descriptorType=vk.VK_DESCRIPTOR_TYPE_STORAGE_BUFFER,
descriptorCount=1,
stageFlags=vk.VK_SHADER_STAGE_COMPUTE_BIT,
))
layout_info = vk.VkDescriptorSetLayoutCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_DESCRIPTOR_SET_LAYOUT_CREATE_INFO,
bindingCount=len(bindings),
pBindings=bindings,
)
self.brain_desc_layout = vk.vkCreateDescriptorSetLayout(self.device, layout_info, None)
pipe_layout_info = vk.VkPipelineLayoutCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_PIPELINE_LAYOUT_CREATE_INFO,
setLayoutCount=1,
pSetLayouts=[self.brain_desc_layout],
pushConstantRangeCount=0,
pPushConstantRanges=[],
)
self.brain_layout = vk.vkCreatePipelineLayout(self.device, pipe_layout_info, None)
stage_info = vk.VkPipelineShaderStageCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_PIPELINE_SHADER_STAGE_CREATE_INFO,
stage=vk.VK_SHADER_STAGE_COMPUTE_BIT,
module=shader_module,
pName="main",
)
pipe_create_info = vk.VkComputePipelineCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_COMPUTE_PIPELINE_CREATE_INFO,
stage=stage_info,
layout=self.brain_layout,
)
self.brain_pipeline = vk.vkCreateComputePipelines(self.device, vk.VK_NULL_HANDLE, 1, [pipe_create_info], None)[0]
vk.vkDestroyShaderModule(self.device, shader_module, None)
def _init_plasticity_pipeline(self):
spv_path = resource("shaders/plasticity.spv")
if not os.path.exists(spv_path):
raise FileNotFoundError(f"SPIR-V compute shader missing: {spv_path}")
with open(spv_path, "rb") as f:
code = f.read()
mod_info = vk.VkShaderModuleCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_SHADER_MODULE_CREATE_INFO,
codeSize=len(code),
pCode=code,
)
shader_module = vk.vkCreateShaderModule(self.device, mod_info, None)
bindings = []
for b_idx in range(6):
bindings.append(vk.VkDescriptorSetLayoutBinding(
binding=b_idx,
descriptorType=vk.VK_DESCRIPTOR_TYPE_STORAGE_BUFFER,
descriptorCount=1,
stageFlags=vk.VK_SHADER_STAGE_COMPUTE_BIT,
))
layout_info = vk.VkDescriptorSetLayoutCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_DESCRIPTOR_SET_LAYOUT_CREATE_INFO,
bindingCount=len(bindings),
pBindings=bindings,
)
self.plasticity_desc_layout = vk.vkCreateDescriptorSetLayout(self.device, layout_info, None)
pipe_layout_info = vk.VkPipelineLayoutCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_PIPELINE_LAYOUT_CREATE_INFO,
setLayoutCount=1,
pSetLayouts=[self.plasticity_desc_layout],
pushConstantRangeCount=0,
pPushConstantRanges=[],
)
self.plasticity_layout = vk.vkCreatePipelineLayout(self.device, pipe_layout_info, None)
stage_info = vk.VkPipelineShaderStageCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_PIPELINE_SHADER_STAGE_CREATE_INFO,
stage=vk.VK_SHADER_STAGE_COMPUTE_BIT,
module=shader_module,
pName="main",
)
pipe_create_info = vk.VkComputePipelineCreateInfo(
sType=vk.VK_STRUCTURE_TYPE_COMPUTE_PIPELINE_CREATE_INFO,
stage=stage_info,
layout=self.plasticity_layout,
)
self.plasticity_pipeline = vk.vkCreateComputePipelines(self.device, vk.VK_NULL_HANDLE, 1, [pipe_create_info], None)[0]
vk.vkDestroyShaderModule(self.device, shader_module, None)
def load_circuit(
self,
row_offsets: np.ndarray,
col_indices: np.ndarray,
weights: np.ndarray,
initial_potentials: Optional[np.ndarray] = None,
initial_spikes: Optional[np.ndarray] = None,
initial_refractory: Optional[np.ndarray] = None
):
"""
Allocates persistent GPU device buffers and writes persistent descriptor sets.
Avoids all per-step buffer allocations.
"""
self.free_circuit_resources()
N = len(row_offsets) - 1
M = len(col_indices)
self.num_neurons = N
self.num_synapses = M
row_offsets = np.ascontiguousarray(row_offsets, dtype=np.int32)
col_indices = np.ascontiguousarray(col_indices, dtype=np.int32)
weights = np.ascontiguousarray(weights, dtype=np.float32)
if initial_potentials is None:
initial_potentials = np.zeros(N, dtype=np.float32)
if initial_spikes is None:
initial_spikes = np.zeros(N, dtype=np.float32)
if initial_refractory is None:
initial_refractory = np.zeros(N, dtype=np.int32)
initial_potentials = np.ascontiguousarray(initial_potentials, dtype=np.float32)
initial_spikes = np.ascontiguousarray(initial_spikes, dtype=np.float32)
initial_ext = np.zeros(N, dtype=np.float32)
initial_ref = np.ascontiguousarray(initial_refractory, dtype=np.int32)
# 1. Allocate persistent buffers
def alloc_and_upload(name: str, arr: np.ndarray):
buf, mem, sz = self._create_buffer(arr.nbytes, vk.VK_BUFFER_USAGE_STORAGE_BUFFER_BIT)
ptr = vk.vkMapMemory(self.device, mem, 0, arr.nbytes, 0)
ptr[0:arr.nbytes] = arr.tobytes()
vk.vkUnmapMemory(self.device, mem)
self.persistent_buffers[name] = {"buf": buf, "mem": mem, "size": sz, "bytes": arr.nbytes}
alloc_and_upload("row_offsets", row_offsets)
alloc_and_upload("col_indices", col_indices)
alloc_and_upload("weights", weights)
alloc_and_upload("prev_spikes", initial_spikes)
alloc_and_upload("ext_inputs", initial_ext)
alloc_and_upload("potentials_in", initial_potentials)
alloc_and_upload("refractory_in", initial_ref)
alloc_and_upload("potentials_out", initial_potentials)
alloc_and_upload("spikes_out", initial_spikes)
alloc_and_upload("refractory_out", initial_ref)
# Params buffer: N, decay, threshold, v_reset, v_rest, t_ref
params_bytes = struct.pack('iffffi', N, 0.85, 1.0, 0.0, 0.0, 2)
p_buf, p_mem, p_sz = self._create_buffer(len(params_bytes), vk.VK_BUFFER_USAGE_STORAGE_BUFFER_BIT)
ptr = vk.vkMapMemory(self.device, p_mem, 0, len(params_bytes), 0)
ptr[0:len(params_bytes)] = params_bytes
vk.vkUnmapMemory(self.device, p_mem)
self.persistent_buffers["brain_params"] = {"buf": p_buf, "mem": p_mem, "size": p_sz, "bytes": len(params_bytes)}
# Plasticity params buffer: M, N, lr, reward, weight_decay, min_w, max_w
plas_bytes = struct.pack('iifffff', M, N, 0.05, 0.0, 0.01, 0.01, 1.0)
pl_buf, pl_mem, pl_sz = self._create_buffer(len(plas_bytes), vk.VK_BUFFER_USAGE_STORAGE_BUFFER_BIT)
self.persistent_buffers["plasticity_params"] = {"buf": pl_buf, "mem": pl_mem, "size": pl_sz, "bytes": len(plas_bytes)}
# 2. Allocate persistent descriptor set for brain step
b_alloc_info = vk.VkDescriptorSetAllocateInfo(
sType=vk.VK_STRUCTURE_TYPE_DESCRIPTOR_SET_ALLOCATE_INFO,
descriptorPool=self.descriptor_pool,
descriptorSetCount=1,
pSetLayouts=[self.brain_desc_layout],
)
self.brain_descriptor_set = vk.vkAllocateDescriptorSets(self.device, b_alloc_info)[0]
# Bindings 0..10
ordered_keys = [
"row_offsets", "col_indices", "weights", "prev_spikes", "ext_inputs",
"potentials_in", "refractory_in", "potentials_out", "spikes_out", "refractory_out", "brain_params"
]
writes = []
for b_idx, key in enumerate(ordered_keys):
b_item = self.persistent_buffers[key]
b_info = vk.VkDescriptorBufferInfo(buffer=b_item["buf"], offset=0, range=b_item["size"])
writes.append(vk.VkWriteDescriptorSet(
sType=vk.VK_STRUCTURE_TYPE_WRITE_DESCRIPTOR_SET,
dstSet=self.brain_descriptor_set,
dstBinding=b_idx,
dstArrayElement=0,
descriptorCount=1,
descriptorType=vk.VK_DESCRIPTOR_TYPE_STORAGE_BUFFER,
pBufferInfo=[b_info],
))
vk.vkUpdateDescriptorSets(self.device, len(writes), writes, 0, None)
# 3. Allocate persistent descriptor set for plasticity step
# Bindings 0..5: RowOffsets, ColIndices, Weights, SpikesOut (post), PrevSpikes (pre), PlasticityParams
p_alloc_info = vk.VkDescriptorSetAllocateInfo(
sType=vk.VK_STRUCTURE_TYPE_DESCRIPTOR_SET_ALLOCATE_INFO,
descriptorPool=self.descriptor_pool,
descriptorSetCount=1,
pSetLayouts=[self.plasticity_desc_layout],
)
self.plasticity_descriptor_set = vk.vkAllocateDescriptorSets(self.device, p_alloc_info)[0]
plas_keys = ["row_offsets", "col_indices", "weights", "spikes_out", "prev_spikes", "plasticity_params"]
plas_writes = []
for b_idx, key in enumerate(plas_keys):
b_item = self.persistent_buffers[key]
b_info = vk.VkDescriptorBufferInfo(buffer=b_item["buf"], offset=0, range=b_item["size"])
plas_writes.append(vk.VkWriteDescriptorSet(
sType=vk.VK_STRUCTURE_TYPE_WRITE_DESCRIPTOR_SET,
dstSet=self.plasticity_descriptor_set,
dstBinding=b_idx,
dstArrayElement=0,
descriptorCount=1,
descriptorType=vk.VK_DESCRIPTOR_TYPE_STORAGE_BUFFER,
pBufferInfo=[b_info],
))
vk.vkUpdateDescriptorSets(self.device, len(plas_writes), plas_writes, 0, None)
# 4. Allocate persistent command buffer
cb_alloc = vk.VkCommandBufferAllocateInfo(
sType=vk.VK_STRUCTURE_TYPE_COMMAND_BUFFER_ALLOCATE_INFO,
commandPool=self.command_pool,
level=vk.VK_COMMAND_BUFFER_LEVEL_PRIMARY,
commandBufferCount=1,
)
self.brain_command_buffer = vk.vkAllocateCommandBuffers(self.device, cb_alloc)[0]
def run_step_persistent(
self,
external_inputs: Optional[np.ndarray] = None,
decay: float = 0.85,
threshold: float = 1.0,
v_reset: float = 0.0,
v_rest: float = 0.0,
t_ref: int = 2,
readback: bool = True
) -> Tuple[Optional[np.ndarray], Optional[np.ndarray], Optional[np.ndarray]]:
"""
Executes one LIF simulation step entirely on GPU using persistent resources.
Zero buffer allocation or descriptor reallocation.
Returns authoritative GPU state (potentials, spikes, refractory) — callers
must use the returned refractory counters, never recompute them locally.
"""
if not self.persistent_buffers:
raise RuntimeError("No circuit loaded in Vulkan compute engine!")
N = self.num_neurons
t0 = time.perf_counter_ns()
# Update external inputs if provided
if external_inputs is not None:
ext_bytes = np.ascontiguousarray(external_inputs, dtype=np.float32).tobytes()
ext_mem = self.persistent_buffers["ext_inputs"]["mem"]
ptr = vk.vkMapMemory(self.device, ext_mem, 0, len(ext_bytes), 0)
ptr[0:len(ext_bytes)] = ext_bytes
vk.vkUnmapMemory(self.device, ext_mem)
# Update params struct
p_bytes = struct.pack('iffffi', N, decay, threshold, v_reset, v_rest, t_ref)
p_mem = self.persistent_buffers["brain_params"]["mem"]
ptr = vk.vkMapMemory(self.device, p_mem, 0, len(p_bytes), 0)
ptr[0:len(p_bytes)] = p_bytes
vk.vkUnmapMemory(self.device, p_mem)
# Record command buffer
cmd = self.brain_command_buffer
vk.vkResetCommandBuffer(cmd, 0)
begin_info = vk.VkCommandBufferBeginInfo(
sType=vk.VK_STRUCTURE_TYPE_COMMAND_BUFFER_BEGIN_INFO,
flags=vk.VK_COMMAND_BUFFER_USAGE_ONE_TIME_SUBMIT_BIT,
)
vk.vkBeginCommandBuffer(cmd, begin_info)
vk.vkCmdBindPipeline(cmd, vk.VK_PIPELINE_BIND_POINT_COMPUTE, self.brain_pipeline)
vk.vkCmdBindDescriptorSets(cmd, vk.VK_PIPELINE_BIND_POINT_COMPUTE, self.brain_layout, 0, 1, [self.brain_descriptor_set], 0, None)
group_count = (N + 63) // 64
vk.vkCmdDispatch(cmd, group_count, 1, 1)
# Pipeline barrier to ensure outputs are written before copying for next step
barrier = vk.VkMemoryBarrier(
sType=vk.VK_STRUCTURE_TYPE_MEMORY_BARRIER,
srcAccessMask=vk.VK_ACCESS_SHADER_WRITE_BIT,
dstAccessMask=vk.VK_ACCESS_SHADER_READ_BIT | vk.VK_ACCESS_HOST_READ_BIT,
)
vk.vkCmdPipelineBarrier(
cmd,
vk.VK_PIPELINE_STAGE_COMPUTE_SHADER_BIT,
vk.VK_PIPELINE_STAGE_COMPUTE_SHADER_BIT | vk.VK_PIPELINE_STAGE_HOST_BIT,
0,
1, [barrier],
0, None,
0, None
)
# Ping-pong copy on GPU: potentials_out -> potentials_in, spikes_out -> prev_spikes, refractory_out -> refractory_in
copy_pot = vk.VkBufferCopy(srcOffset=0, dstOffset=0, size=N * 4)
vk.vkCmdCopyBuffer(cmd, self.persistent_buffers["potentials_out"]["buf"], self.persistent_buffers["potentials_in"]["buf"], 1, [copy_pot])
vk.vkCmdCopyBuffer(cmd, self.persistent_buffers["spikes_out"]["buf"], self.persistent_buffers["prev_spikes"]["buf"], 1, [copy_pot])
vk.vkCmdCopyBuffer(cmd, self.persistent_buffers["refractory_out"]["buf"], self.persistent_buffers["refractory_in"]["buf"], 1, [copy_pot])
vk.vkEndCommandBuffer(cmd)
submit_info = vk.VkSubmitInfo(
sType=vk.VK_STRUCTURE_TYPE_SUBMIT_INFO,
commandBufferCount=1,
pCommandBuffers=[cmd],
)
vk.vkQueueSubmit(self.queue, 1, [submit_info], vk.VK_NULL_HANDLE)
vk.vkQueueWaitIdle(self.queue)
t1 = time.perf_counter_ns()
self.last_step_latency_ms = (t1 - t0) / 1_000_000.0
self.total_steps_executed += 1
if readback:
# Read back state from host-coherent buffer
pot_mem = self.persistent_buffers["potentials_out"]["mem"]
spk_mem = self.persistent_buffers["spikes_out"]["mem"]
ref_mem = self.persistent_buffers["refractory_out"]["mem"]
ptr = vk.vkMapMemory(self.device, pot_mem, 0, N * 4, 0)
pot_out = np.frombuffer(bytes(ptr[0:N * 4]), dtype=np.float32).copy()
vk.vkUnmapMemory(self.device, pot_mem)
ptr = vk.vkMapMemory(self.device, spk_mem, 0, N * 4, 0)
spk_out = np.frombuffer(bytes(ptr[0:N * 4]), dtype=np.float32).copy()
vk.vkUnmapMemory(self.device, spk_mem)
ptr = vk.vkMapMemory(self.device, ref_mem, 0, N * 4, 0)
ref_out = np.frombuffer(bytes(ptr[0:N * 4]), dtype=np.int32).copy()
vk.vkUnmapMemory(self.device, ref_mem)
return pot_out, spk_out, ref_out
return None, None, None
def run_plasticity_persistent(
self,
learning_rate: float = 0.05,
reward: float = 1.0,
weight_decay: float = 0.01,
min_weight: float = 0.01,
max_weight: float = 1.0,
readback: bool = False
) -> Optional[np.ndarray]:
"""
Executes synaptic plasticity step on GPU-resident weights in-place.
"""
if not self.persistent_buffers:
return None
M = self.num_synapses
t0 = time.perf_counter_ns()
# Update plasticity parameters
M = self.num_synapses
N = self.num_neurons
pl_bytes = struct.pack('iifffff', M, N, learning_rate, reward, weight_decay, min_weight, max_weight)
pl_mem = self.persistent_buffers["plasticity_params"]["mem"]
ptr = vk.vkMapMemory(self.device, pl_mem, 0, len(pl_bytes), 0)
ptr[0:len(pl_bytes)] = pl_bytes
vk.vkUnmapMemory(self.device, pl_mem)
cmd = self.brain_command_buffer
vk.vkResetCommandBuffer(cmd, 0)
begin_info = vk.VkCommandBufferBeginInfo(
sType=vk.VK_STRUCTURE_TYPE_COMMAND_BUFFER_BEGIN_INFO,
flags=vk.VK_COMMAND_BUFFER_USAGE_ONE_TIME_SUBMIT_BIT,
)
vk.vkBeginCommandBuffer(cmd, begin_info)
vk.vkCmdBindPipeline(cmd, vk.VK_PIPELINE_BIND_POINT_COMPUTE, self.plasticity_pipeline)
vk.vkCmdBindDescriptorSets(cmd, vk.VK_PIPELINE_BIND_POINT_COMPUTE, self.plasticity_layout, 0, 1, [self.plasticity_descriptor_set], 0, None)
group_count = (M + 63) // 64
vk.vkCmdDispatch(cmd, group_count, 1, 1)
barrier = vk.VkMemoryBarrier(
sType=vk.VK_STRUCTURE_TYPE_MEMORY_BARRIER,
srcAccessMask=vk.VK_ACCESS_SHADER_WRITE_BIT,
dstAccessMask=vk.VK_ACCESS_SHADER_READ_BIT | vk.VK_ACCESS_HOST_READ_BIT,
)
vk.vkCmdPipelineBarrier(
cmd,
vk.VK_PIPELINE_STAGE_COMPUTE_SHADER_BIT,
vk.VK_PIPELINE_STAGE_COMPUTE_SHADER_BIT | vk.VK_PIPELINE_STAGE_HOST_BIT,
0,
1, [barrier],
0, None,
0, None
)
vk.vkEndCommandBuffer(cmd)
submit_info = vk.VkSubmitInfo(
sType=vk.VK_STRUCTURE_TYPE_SUBMIT_INFO,
commandBufferCount=1,
pCommandBuffers=[cmd],
)
vk.vkQueueSubmit(self.queue, 1, [submit_info], vk.VK_NULL_HANDLE)
vk.vkQueueWaitIdle(self.queue)
t1 = time.perf_counter_ns()
self.last_plasticity_latency_ms = (t1 - t0) / 1_000_000.0
if readback:
w_mem = self.persistent_buffers["weights"]["mem"]
ptr = vk.vkMapMemory(self.device, w_mem, 0, M * 4, 0)
weights_out = np.frombuffer(bytes(ptr[0:M * 4]), dtype=np.float32).copy()
vk.vkUnmapMemory(self.device, w_mem)
return weights_out
return None
def download_weights(self) -> Optional[np.ndarray]:
"""Pure GPU->CPU weight readback with no dispatch (sync primitive).
Used for lazy weight synchronization: GPU weights stay authoritative
across steps; the CPU mirror is refreshed only at explicit sync points
(snapshots, experiment manifests, validation), never per step.
"""
if not self.persistent_buffers:
return None
import numpy as _np
M = self.num_synapses
w_mem = self.persistent_buffers["weights"]["mem"]
ptr = vk.vkMapMemory(self.device, w_mem, 0, M * 4, 0)
out = _np.frombuffer(bytes(ptr[0:M * 4]), dtype=_np.float32).copy()
vk.vkUnmapMemory(self.device, w_mem)
return out
def upload_buffer_data(self, name: str, arr: np.ndarray):
"""Uploads contiguous numpy array data to an existing persistent GPU buffer."""
if name in self.persistent_buffers:
b_item = self.persistent_buffers[name]
arr_bytes = np.ascontiguousarray(arr).tobytes()
copy_len = min(len(arr_bytes), b_item["bytes"])
ptr = vk.vkMapMemory(self.device, b_item["mem"], 0, copy_len, 0)
ptr[0:copy_len] = arr_bytes[:copy_len]
vk.vkUnmapMemory(self.device, b_item["mem"])
def run_step(
self,
row_offsets: np.ndarray,
col_indices: np.ndarray,
weights: np.ndarray,
prev_activations: np.ndarray,
external_inputs: np.ndarray,
potentials_in: np.ndarray,
decay: float = 0.85,
threshold: float = 1.0,
leak: float = 0.05
) -> Tuple[np.ndarray, np.ndarray]:
"""
Legacy / test harness compatibility method:
Loads circuit if not loaded, updates persistent buffers with provided inputs, executes step, and returns (potentials, spikes).
"""
N = len(potentials_in)
if (not self.persistent_buffers) or (self.num_neurons != N) or (self.num_synapses != len(weights)):
self.load_circuit(row_offsets, col_indices, weights, potentials_in, prev_activations)
else:
self.upload_buffer_data("weights", weights)
self.upload_buffer_data("prev_spikes", prev_activations)
self.upload_buffer_data("potentials_in", potentials_in)
self.upload_buffer_data("refractory_in", np.zeros(N, dtype=np.int32))
pot_out, spk_out, _ = self.run_step_persistent(
external_inputs=external_inputs,
decay=decay,
threshold=threshold,
readback=True
)
return pot_out, spk_out
def run_plasticity_step(
self,
row_offsets: np.ndarray,
col_indices: np.ndarray,
weights: np.ndarray,
post_activations: np.ndarray,
pre_activations: np.ndarray,
learning_rate: float = 0.05,
reward: float = 1.0,
weight_decay: float = 0.01,
min_weight: float = 0.01,
max_weight: float = 1.0
) -> np.ndarray:
"""
Legacy / test harness compatibility method:
Executes plasticity step and returns updated weights.
"""
if (not self.persistent_buffers) or (self.num_synapses != len(weights)):
self.load_circuit(row_offsets, col_indices, weights, None, pre_activations)
else:
self.upload_buffer_data("weights", weights)
self.upload_buffer_data("prev_spikes", pre_activations)
self.upload_buffer_data("spikes_out", post_activations)
w_out = self.run_plasticity_persistent(
learning_rate=learning_rate,
reward=reward,
weight_decay=weight_decay,
min_weight=min_weight,
max_weight=max_weight,
readback=True
)
return w_out if w_out is not None else weights
def get_diagnostics(self) -> Dict[str, Any]:
"""Returns real live hardware diagnostics and performance telemetry."""
total_mem_allocated = sum(b["bytes"] for b in self.persistent_buffers.values()) if self.persistent_buffers else 0
steps_per_sec = round(1000.0 / max(0.001, self.last_step_latency_ms), 1) if self.last_step_latency_ms > 0 else 0.0
neurons_per_sec = int(steps_per_sec * self.num_neurons)
synapses_per_sec = int(steps_per_sec * self.num_synapses)
return {
"device_name": self.device_name,
"device_type": int(self.device_type),
"device_type_str": self.device_type_str,
"driver_version": int(self.driver_version),
"queue_family_idx": self.queue_family_idx,
"total_gpu_memory_allocated_bytes": total_mem_allocated,
"step_latency_ms": round(self.last_step_latency_ms, 3),
"plasticity_latency_ms": round(self.last_plasticity_latency_ms, 3),
"throughput_steps_per_sec": steps_per_sec,
"throughput_neurons_per_sec": neurons_per_sec,
"throughput_synapses_per_sec": synapses_per_sec,
"total_steps_executed": self.total_steps_executed,
"status": "OPERATIONAL"
}
def free_circuit_resources(self):
"""Frees persistent circuit buffers and descriptor sets."""
if self.device is None:
return
if self.brain_command_buffer is not None:
vk.vkFreeCommandBuffers(self.device, self.command_pool, 1, [self.brain_command_buffer])
self.brain_command_buffer = None
if self.brain_descriptor_set is not None:
vk.vkFreeDescriptorSets(self.device, self.descriptor_pool, 1, [self.brain_descriptor_set])
self.brain_descriptor_set = None
if self.plasticity_descriptor_set is not None:
vk.vkFreeDescriptorSets(self.device, self.descriptor_pool, 1, [self.plasticity_descriptor_set])
self.plasticity_descriptor_set = None
for name, item in self.persistent_buffers.items():
vk.vkDestroyBuffer(self.device, item["buf"], None)
vk.vkFreeMemory(self.device, item["mem"], None)
self.persistent_buffers.clear()
def cleanup(self):
"""Full cleanup of all Vulkan resources."""
if self.device is None:
return
vk.vkDeviceWaitIdle(self.device)
self.free_circuit_resources()
if self.descriptor_pool:
vk.vkDestroyDescriptorPool(self.device, self.descriptor_pool, None)
self.descriptor_pool = None
if self.brain_pipeline:
vk.vkDestroyPipeline(self.device, self.brain_pipeline, None)
self.brain_pipeline = None
if self.brain_layout:
vk.vkDestroyPipelineLayout(self.device, self.brain_layout, None)
self.brain_layout = None
if self.brain_desc_layout:
vk.vkDestroyDescriptorSetLayout(self.device, self.brain_desc_layout, None)
self.brain_desc_layout = None
if self.plasticity_pipeline:
vk.vkDestroyPipeline(self.device, self.plasticity_pipeline, None)
self.plasticity_pipeline = None
if self.plasticity_layout:
vk.vkDestroyPipelineLayout(self.device, self.plasticity_layout, None)
self.plasticity_layout = None
if self.plasticity_desc_layout:
vk.vkDestroyDescriptorSetLayout(self.device, self.plasticity_desc_layout, None)
self.plasticity_desc_layout = None
if self.command_pool:
vk.vkDestroyCommandPool(self.device, self.command_pool, None)
self.command_pool = None
if self.device:
vk.vkDestroyDevice(self.device, None)
self.device = None
if self.instance:
vk.vkDestroyInstance(self.instance, None)
self.instance = None
VulkanBrainBackend = VulkanComputeEngine
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