6.5 KiB
HCQ Compatible Runtime
Overview
The main aspect of HCQ-compatible runtimes is how they interact with devices. In HCQ, all interactions with devices occur in a hardware-friendly manner using command queues. This approach allows commands to be issued directly to devices, bypassing runtime overhead such as HIP or CUDA. Additionally, by using the HCQ API, these runtimes can benefit from various optimizations and features, including HCQGraph and built-in profiling capabilities.
Command Queues
To interact with devices, there are 2 types of queues: HWComputeQueue
and HWCopyQueue
. Commands which are defined in a base HWCommandQueue
class should be supported by both queues. These methods are timestamp and synchronization methods like signal and wait.
For example, the following Python code enqueues a wait, execute, and signal command on the HCQ-compatible device:
HWComputeQueue().wait(signal_to_wait, value_to_wait) \
.exec(program, args_state, global_dims, local_dims) \
.signal(signal_to_fire, value_to_fire) \
.submit(your_device)
Each runtime should implement the required functions that are defined in the HWCommandQueue
, HWComputeQueue
, and HWCopyQueue
classes.
::: tinygrad.device.HWCommandQueue options: members: [ "signal", "wait", "timestamp", "update_signal", "update_wait", "bind", "submit", ] show_source: false
::: tinygrad.device.HWComputeQueue options: members: [ "memory_barrier", "exec", "update_exec", ] show_source: false
::: tinygrad.device.HWCopyQueue options: members: [ "copy", "update_copy", ] show_source: false
Implementing custom commands
To implement custom commands in the queue, use the @hcq_command decorator for your command implementations.
::: tinygrad.device.hcq_command options: members: [ "copy", "update_copy", ] show_source: false
HCQ Compatible Device
The HCQCompiled
class defines the API for HCQ-compatible devices. This class serves as an abstract base class that device-specific implementations should inherit from and implement.
::: tinygrad.device.HCQCompiled options: show_source: false
Signals
Signals are device-dependent structures used for synchronization and timing in HCQ-compatible devices. They should be designed to record both a value
and a timestamp
within the same signal. HCQ-compatible backend implementations should use HCQSignal
as a base class.
::: tinygrad.device.HCQSignal options: members: [value, timestamp, wait] show_source: false
The following Python code demonstrates the usage of signals:
signal = your_device.signal_t()
HWComputeQueue().timestamp(signal) \
.signal(signal, value_to_fire) \
.submit(your_device)
signal.wait(value_to_fire)
signaled_value = signal.value # should be the same as `value_to_fire`
timestamp = signal.timestamp
Synchronization signals
Each HCQ-compatible device must allocate two signals for global synchronization purposes. These signals are passed to the HCQCompiled
base class during initialization: an active timeline signal self.timeline_signal
and a shadow timeline signal self._shadow_timeline_signal
which helps to handle signal value overflow issues. You can find more about synchronization in the synchronization section
HCQ Compatible Allocator
The HCQAllocator
base class simplifies allocator logic by leveraging command queues abstractions. This class efficiently handles copy and transfer operations, leaving only the alloc and free functions to be implemented by individual backends.
::: tinygrad.device.HCQAllocator options: members: [ "_alloc", "_free", ] show_source: false
HCQ Allocator Result Protocol
Backends must adhere to the HCQBuffer
protocol when returning allocation results.
::: tinygrad.device.HCQBuffer options: members: true show_source: false
HCQ Compatible Program
HCQProgram
is a base class for defining programs compatible with HCQ-enabled devices. It provides a flexible framework for handling different argument layouts (see HCQArgsState
).
::: tinygrad.device.HCQProgram options: members: true show_source: false
Arguments State
HCQArgsState
is a base class for managing the argument state for HCQ programs. Backend implementations should create a subclass of HCQArgsState
to manage arguments for the given program.
::: tinygrad.device.HCQArgsState options: members: true show_source: false
Lifetime: The HCQArgsState
is passed to HWComputeQueue.exec
and is guaranteed not to be freed until HWComputeQueue.submit
for the same queue is called.
Synchronization
HCQ-compatible devices use a global timeline signal for synchronizing all operations. This mechanism ensures proper ordering and completion of tasks across the device. By convention, self.timeline_value
points to the next value to signal. So, to wait for all previous operations on the device to complete, wait for self.timeline_value - 1
value. The following Python code demonstrates the typical usage of signals to synchronize execution to other operations on the device:
HWComputeQueue().wait(your_device.timeline_signal, your_device.timeline_value - 1) \
.exec(...)
.signal(your_device.timeline_signal, your_device.timeline_value) \
.submit(your_device)
your_device.timeline_value += 1
# Optionally wait for execution
your_device.timeline_signal.wait(your_device.timeline_value - 1)
HCQGraph
HCQGraph is a core feature that implements GraphRunner
for HCQ-compatible devices. HCQGraph
builds a static HWComputeQueue
and HWCopyQueue
for all operations per device. To optimize enqueue time, only the necessary parts of the queues are updated for each run using the update APIs of the queues, avoiding a complete rebuild.
Optionally, queues can implement a bind
API, which allows further optimization by eliminating the need to copy the queues into the device ring.