This commit removes the `LIBOMPTARGET_SHARED_MEMORY_SIZE` envar and
outputs a runtime warning if it is defined. Access to dynamic shared memory
should be obtained through the `dyn_groupprivate` clause (OpenMP 6.1) or
the launch arguments in liboffload kernel launch.
Summary:
We use this `dyn_ptr` argument in Clang/OpenMP to handle the
`KernelLaunchEnvironment`. This is a per-kernel argument used to share
some information. Currenetly, it's prepended to the argument list and we
generate storage for it in the runtime.
This is bad for a few reasons:
1. It changes the ABI by shifting user arguments
2. It cannot be trivially be left uninitialized if unused
3. The runtime must allocate its own memory for it
This PR changes it to be appended instead. Additionally, space for this
is always emitted. This means the OMPIRBuilder itself will provide the
storage, we simply need to populate it in the runtime if it is used.
This means that if it's unused we don't always pay the cost and it's
easier for non-OpenMP users to ignore it.
Backward compatibility is maintained by auto-upgrading the kernel
arguments. In `libomptarget` we completely allocate a new buffer to
store this in the new format. The plugins still need to respect the old
ABI of the called device object, so we simply rotate it if it's the old
version.
As discussed in #185404 we might want to provide a way for plugins to
validate images not recognized by the common layer.
This PR adds such extension and uses it to validate pure SPIRV images by
the Level Zero plugin.
Summary:
This was a regression from the original LLVM-gpu-loader. We used to
handle `-mwavefrontsize64` correctly in the loader by over-allocating
memory and just leaving the upper 32-bits masked off. In order to handle
this in offload we need to scan loaded kernels to see how much memory we
need to allocate. This should be safe, the protocol is designed to
handle an arbitrary size and worst-case this just wastes space.
Summary:
This PR provides the minimal support for Fortran I/O coming from a GPU
in OpenMP offloading. We use the same support the `libc` uses for its
printing through the RPC server. The helper functions `rpc::dispatch`
and `rpc::invoke` help make this mostly automatic.
Becaus Fortran I/O is not reentrant, the vast majority of complexity
comes from needing to stitch together calls from the GPU until they can
be executed all at once. This is needed not only because of the
limitations of recursive I/O, but without this the output would all be
interleaved because of the GPU's lock-step execution.
As such, the return values from the intermediate functions are
meaningless, all returning true. The final value is correct however. For
cookies we create a context pointer on the server to chain these
together.
Works on both my AMD and NVIDIA GPUs.
```fortran
program hello_gpu
implicit none
!$omp target teams num_teams(1)
!$omp parallel num_threads(2)
! Print strings
print *, "Hello from GPU"
!$omp end parallel
!$omp end target teams
end program hello_gpu
```
```console
> flang hello.f90 -O2 -fopenmp --offload-arch=gfx1030
> ./a.out
Hello from GPU
Hello from GPU
> flang hello.f90 -O2 -fopenmp --offload-arch=sm_89
> ./a.out
Hello from GPU
Hello from GPU
```
This PR adds extends liboffload olMemRegister API to handle a case when
a memory block may have been mapped before calling olMemRegister to
support some use cases in libomptarget
Summary:
Closing ports was previously done manually, This makes the protocol more
error prone as unclosed ports will leak and eventually the locks will
run out. I believe the original fear was that the RAII portion would
negatively impact code generation but I have not noticed anything
significant.
Summary:
The static object mixes callbacks from different plugins because ever
since we moved to the object library target these are actually shared.
Just make it a member of the base class and make it a pointer set just
to do some basic deduplication.
Summary:
We provide an RPC server to manage calls initiated by the device to run
on the host. This is very useful for the built-in handling we have,
however there are cases where we would want to extend this
functionality.
Cases like Fortran or MPI would be useful, but we cannot put references
to these in the core offloading runtime. This way, we can provide this
as a library interface that registers custom handlers for whatever code
people want.
There are a few places where data types based on character array or
string are printed in the debug message while they do not represent
strings. Such expressions should be casted to `void *` unless they
represent actual strings. Change also includes casting from integral
type to pointer type when appropriate.
Add liboffload asynchronous queue query API for libomptarget migration
This PR adds liboffload asynchronous queue query API that needed to make
libomptarget to use liboffload
Add a new nextgen plugin that supports GPU devices through the Intel oneAPI Level Zero library. The plugin is not enabled by default and needs to be added to LIBOMPTARGET_PLUGINS_TO_BUILD explicitely.
---------
Co-authored-by: Alexey Sachkov <alexey.sachkov@intel.com>
Co-authored-by: Nick Sarnie <nick.sarnie@intel.com>
Co-authored-by: Joseph Huber <huberjn@outlook.com>
Update debug messages based on the new method from #170425. Updated the
following files.
- plugins-nextgen/common/include/MemoryManager.h
- plugins-nextgen/common/include/PluginInterface.h
- plugins-nextgen/common/src/GlobalHandler.cpp
- plugins-nextgen/common/src/PluginInterface.cpp
- plugins-nextgen/host/dynamic_ffi/ffi.cpp
Summary:
We start this thread if the RPC client symbol is detected in the loaded
binary. We should make this sleep if there's no work to avoid the thread
running at high priority when the (scarecely used) RPC call is actually
required. So, right now after 25 microseconds we will assume the server
is inactive and begin sleeping. This resets once we do find work.
AMD supports a more intelligent way to do this. HSA signals can wake a
sleeping thread from the kernel, and signals can be sent from the GPU
side. This would be nice to have and I'm planning on working with it in
the future to make this infrastructure more usable with existing AMD
workloads.
Summary:
This was a lot of code that was only used for upstream LLVM builds of
AMDGPU offloading. We have a generic and fast `malloc` in `libc` now so
just use that. Simplifies code, can be added back if we start providing
alternate forms but I don't think there's a single use-case that would
justify it yet.
Introduced in OpenMP 6.0, the device UID shall be a unique identifier of
a device on a given system. (Not necessarily a UUID.) Since it is not
guaranteed that the (U)UIDs defined by the device vendor libraries, such
as HSA, do not overlap with those of other vendors, the device UIDs in
offload are always combined with the offload plugin name. In case the
vendor library does not specify any device UID for a given device, we
fall back to the offload-internal device ID.
The device UID can be retrieved using the `llvm-offload-device-info`
tool.
Adds omp_target_is_accessible routine.
Refactors common code from omp_target_is_present to work for both
routines.
---------
Co-authored-by: Shilei Tian <i@tianshilei.me>
Currently there are two serialization modes for bitstream Remarks:
standalone and separate. The separate mode splits remark metadata (e.g.
the string table) from actual remark data. The metadata is written into
the object file by the AsmPrinter, while the remark data is stored in a
separate remarks file. This means we can't use bitstream remarks with
tools like opt that don't generate an object file. Also, it is confusing
to post-process bitstream remarks files, because only the standalone
files can be read by llvm-remarkutil. We always need to use dsymutil
to convert the separate files to standalone files, which only works for
MachO. It is not possible for clang/opt to directly emit bitstream
remark files in standalone mode, because the string table can only be
serialized after all remarks were emitted.
Therefore, this change completely removes the separate serialization
mode. Instead, the remark string table is now always written to the end
of the remarks file. This requires us to tell the serializer when to
finalize remark serialization. This automatically happens when the
serializer goes out of scope. However, often the remark file goes out of
scope before the serializer is destroyed. To diagnose this, I have added
an assert to alert users that they need to explicitly call
finalizeLLVMOptimizationRemarks.
This change paves the way for further improvements to the remark
infrastructure, including more tooling (e.g. #159784), size optimizations
for bitstream remarks, and more.
Pull Request: https://github.com/llvm/llvm-project/pull/156715
Summary:
This was originally added in as a hack to work around CUDA's limitation
on allocation. The `libc` implementation now isn't even used for CUDA so
this code is never hit. Even if this case, this code never truly worked.
A true solution would be to use CUDA's virtual memory API instead to
allocate 2MiB slabs independenctly from the normal memory management
done in the stream.
Summary:
This exposes the 'isDeviceCompatible' routine for checking if a binary
*can* be loaded. This is useful if people don't want to consume errors
everywhere when figuring out which image to put to what device.
I don't know if this is a good name, I was thining like `olIsCompatible`
or whatever. Let me know what you think.
Long term I'd like to be able to do something similar to what OpenMP
does where we can conditionally only initialize devices if we need them.
That's going to be support needed if we want this to be more
generic.
Currently get this error
```
offload/plugins-nextgen/common/src/PluginInterface.cpp:859:63: error: member reference type 'StringRef' is not a pointer; did you mean to use '.'?
```
We pass the full image binary now so we can't really print anything
useful here.
Seems introduced in https://github.com/llvm/llvm-project/pull/158748.
---------
Signed-off-by: Sarnie, Nick <nick.sarnie@intel.com>
Co-authored-by: Joseph Huber <huberjn@outlook.com>
Summary:
Currently we have this `__tgt_device_image` indirection which just takes
a reference to some pointers. This was all find and good when the only
usage of this was from a section of GPU code that came from an ELF
constant section. However, we have expanded beyond that and now need to
worry about managing lifetimes. We have code that references the image
even after it was loaded internally. This patch changes the
implementation to instaed copy the memory buffer and manage it locally.
This PR reworks the JIT and other image handling to directly manage its
own memory. We now don't need to duplicate this behavior externally at
the Offload API level. Also we actually free these if the user unloads
them.
Upside, less likely to crash and burn. Downside, more latency when
loading an image.
Summary:
This operation is done every time we load a binary, this behavior should
be moved into OpenMP since it concerns an OpenMP specific data struct.
This is a little messy, because ideally we should only be using public
APIs, but more can be extracted later.
Previously, `olDestroyQueue` would not actually destroy the queue,
instead leaving it for the device to clean up when it was destroyed.
Now, the queue is either released immediately if it is complete or put
into a list of "pending" queues if it is not. Whenever we create a new
queue, we check this list to see if any are now completed. If there are
any we release their resources and use them instead of pulling from
the pool.
This prevents long running programs that create and drop many queues
without syncing them from leaking memory all over the place.
This is equivalent to `cuOccupancyMaxPotentialBlockSize`. It is
currently
only implemented on Cuda; AMDGPU and Host return unsupported.
---------
Co-authored-by: Callum Fare <callum@codeplay.com>
The purpose of this fence is to ensure that any `dataSubmit`s inserted
into a queue before a `dataFence` finish before finish before any
`dataSubmit`s
inserted after it begin.
This is a no-op for most queues, since they are in-order, and by design
any operations inserted into them occur in order.
But the interface is supposed to be functional for out-of-order queues.
The addition of the interface means that any operations that rely on
such ordering (like ATTACH map-type support in #149036) can invoke it,
without worrying about whether the underlying queue is in-order or
out-of-order.
Once a plugin supports out-of-order queues, the plugin can implement
this function, without requiring any change at the libomptarget level.
---------
Co-authored-by: Alex Duran <alejandro.duran@intel.com>
This sprinkles a few mutexes around the plugin interface so that the
olLaunchKernel CTS test now passes when ran on multiple threads.
Part of this also involved changing the interface for device synchronise
so that it can optionally not free the underlying queue (which
introduced a race condition in liboffload).
Add a device function to check if a device queue is empty. If liboffload
tries to create an event for an empty queue, we create an "empty" event
that is already complete.
This allows `olCreateEvent`, `olSyncEvent` and `olWaitEvent` to run
quickly for empty queues.
Enables AMD data center class GPUs to use memory manager memory pooling
up to 3GB allocation by default, up from the "1 << 13" threshold that
all plugin-nextgen devices use.
The following patch introduces a new interop interface implementation
with the following characteristics:
* It supports the new 6.0 prefer_type specification
* It supports both explicit objects (from interop constructs) and
implicit objects (from variant calls).
* Implements a per-thread reuse mechanism for implicit objects to reduce
overheads.
* It provides a plugin interface that allows selecting the supported
interop types, and managing all the backend related interop operations
(init, sync, ...).
* It enables cooperation with the OpenMP runtime to allow progress on
OpenMP synchronizations.
* It cleanups some vendor/fr_id mismatchs from the current query
routines.
* It supports extension to define interop callbacks for library cleanup.
