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[FRONTEND] Added on-disk cache for compiled kernels (#287)

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This commit is contained in:
Philippe Tillet
2021-09-18 22:48:26 -07:00
committed by GitHub
parent bd855ac13d
commit 6e5b0b4301
5 changed files with 235 additions and 81 deletions
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131
python/triton/code_gen.py
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@@ -5,6 +5,11 @@ import struct
import sys
import tempfile
import textwrap
import hashlib
import atexit
import os
import shelve
from filelock import FileLock
import torch
import triton
@@ -411,23 +416,31 @@ class CodeGenerator(ast.NodeVisitor):
class Binary:
def __init__(self, backend, module, kernel, asm, num_warps, num_stages, force_nc_cache, shared_mem):
# cache ir asm
def __init__(self, backend, name, asm, shared_mem, num_warps):
self.backend = backend
self.name = name
self.asm = asm
self.module = module
self.kernel = kernel
self.shared_mem = shared_mem
self.num_warps = num_warps
self.num_stages = num_stages
self.force_nc_cache = force_nc_cache
self.sass = None
self.backend = backend
class LoadedBinary:
def __init__(self, device: int, bin: Binary):
module, kernel = _triton.code_gen.load_binary(bin.backend,
bin.name,
bin.asm,
bin.shared_mem,
device)
self.bin = bin
self.asm = bin.asm
self.module = module
self.kernel = kernel
self.device = device
def __call__(self, stream, args, grid_0, grid_1=1, grid_2=1):
_triton.runtime.enqueue(self.backend, stream, self.kernel,
_triton.runtime.enqueue(self.bin.backend, stream, self.kernel,
grid_0, grid_1, grid_2,
self.num_warps * 32, 1, 1,
args, self.shared_mem)
self.bin.num_warps * 32, 1, 1,
args, self.bin.shared_mem)
class CompilationError(Exception):
@@ -536,11 +549,11 @@ class Kernel:
backend = _triton.runtime.backend.CUDA
else:
backend = _triton.runtime.backend.ROCM
mod, ker, asm, shared_mem = _triton.code_gen.compile_ttir(backend, generator.module, device, num_warps, num_stages, force_nc_cache)
name, asm, shared_mem = _triton.code_gen.compile_ttir(backend, generator.module, device, num_warps, num_stages, force_nc_cache)
max_shared_memory = _triton.runtime.max_shared_memory(backend, device)
if shared_mem > max_shared_memory:
raise OutOfResources(shared_mem, max_shared_memory, "shared memory")
return Binary(backend, mod, ker, asm, num_warps, num_stages, force_nc_cache, shared_mem)
return Binary(backend, name, asm, shared_mem, num_warps)
def __call__(self, *wargs, grid, num_warps=4, num_stages=2, force_nc_cache=False, **meta):
# device inference
@@ -579,29 +592,43 @@ class Kernel:
attributes = {i: Kernel.pow2_divisor(a) for i, a in enumerate(args) if isinstance(a, int)}
# transforms ints whose value is one into constants for just-in-time compilation
constants = {i: arg for i, arg in enumerate(wargs) if isinstance(arg, int) and arg == 1}
# determine if we need to re-compile
# compute hash for caching this kernel
types_key = Kernel._types_key(*wargs, tensor_idxs=tensor_idxs)
attr_key = frozenset(attributes.items())
meta_key = frozenset(meta.items())
const_key = frozenset(constants.items())
key = (device_ty, device_idx, types_key, attr_key, num_warps, num_stages, meta_key, const_key)
cache = self.fn.cache
if key not in cache:
# compile and cache configuration if necessary
cache[key] = self._compile(
*wargs, device=device_idx, attributes=attributes,
num_warps=num_warps, num_stages=num_stages, force_nc_cache=force_nc_cache,
constants=constants, **meta
)
key = repr(key)
# get cached binary
drv_cache = self.fn.drv_cache
bin_cache_path = self.fn.bin_cache_path
bin_lock_path = self.fn.bin_lock_path
if key not in drv_cache:
binary = None
if bin_lock_path:
with FileLock(bin_lock_path):
with shelve.open(bin_cache_path) as db:
binary = db.get(key, None)
if binary is None:
binary = self._compile(
*wargs, device=device_idx, attributes=attributes,
num_warps=num_warps, num_stages=num_stages, force_nc_cache=force_nc_cache,
constants=constants, **meta
)
if bin_lock_path:
with FileLock(bin_lock_path):
with shelve.open(bin_cache_path) as db:
db[key] = binary
drv_cache[key] = LoadedBinary(device_idx, binary)
# pack arguments
fmt = ''.join(['P' if i in tensor_idxs else Kernel._type_name(arg.__class__) for i, arg in enumerate(wargs)])
params = struct.pack(fmt, *args)
# enqueue cached function into stream
binary = cache[key]
callable = drv_cache[key]
stream = torch.cuda.current_stream(device_idx).cuda_stream
grid = grid(meta) if hasattr(grid, '__call__') else grid
binary(stream, params, *grid)
return binary
callable(stream, params, *grid)
return callable
class Launcher:
@@ -662,17 +689,59 @@ class Autotuner:
class JITFunction:
# clear cache if the db is older than either the frontend or the backend
def _clear_cache(self):
frontend_mtime = os.path.getmtime(triton.code_gen.__file__)
backend_mtime = os.path.getmtime(triton._C.libtriton.__file__)
with FileLock(self.bin_lock_path):
cache_mtime = os.path.getmtime(self.db_path)
if frontend_mtime > cache_mtime or backend_mtime > cache_mtime:
os.remove(self.db_path)
def _init_cache_paths(self):
# fetch cache directory path
cache_dir = os.environ.get('TRITON_CACHE_DIR', '/tmp/triton/')
if not cache_dir:
self.bin_cache_path = None
self.db_path = None
self.bin_lock_path = None
return
# create cache directory
if not os.path.exists(cache_dir):
os.makedirs(cache_dir)
# create md5 hash of src
md5 = hashlib.md5()
md5.update(self.src.encode('utf-8'))
md5_hash = md5.hexdigest()
# load dbm file in cache_dir for md5_hash
self.bin_cache_path = os.path.join(cache_dir, md5_hash)
self.db_path = self.bin_cache_path + '.db'
self.bin_lock_path = self.bin_cache_path + '.lock'
# if bin_cache_path exists
if os.path.exists(self.db_path):
self._clear_cache()
def __init__(self, fn):
# information of wrapped function
self.fn = fn
self.module = fn.__module__
self.arg_names = inspect.getfullargspec(fn).args
self.cache = dict()
self.src = textwrap.dedent(inspect.getsource(fn))
# cache for callable driver objects (e.g. CUkernel)
self.drv_cache = dict()
# on-disk paths for the binary cache and corresponding
# file-lock
self._init_cache_paths()
# JITFunction can be instantiated as kernel
# when called with a grid using __getitem__
self.kernel_decorators = []
self.src = textwrap.dedent(inspect.getsource(fn))
self.kernel = None
# forward docs
self.__doc__ = fn.__doc__
# we do not parse in the constructor because
# we do not parse `src` in the constructor because
# the user might want to monkey-patch self.src dynamically.
# Some unit tests do this, for example.
def parse(self):
@@ -699,10 +768,16 @@ class JITFunction:
raise e
raise CompilationError(self.src, node, e)
# - when `.src` attribute is set, cache path needs
# to be reinitialized
# - when kernel decorators change, cached kernel
# needs to be cleared
def __setattr__(self, name, value):
if name == 'kernel_decorators':
self.kernel = None
super(JITFunction, self).__setattr__(name, value)
if name == 'src':
self._init_cache_paths()
def _init_kernel(self):
if self.kernel is None: