This release of CompilerGym focuses on backend extensibility and adds a bunch of new features to make it easier to add support for new compilers:
- Adds a new
CompilationSession
class encapsulates a single incremental compilation session (#261). - Adds a common runtime for CompilerGym services that takes a
CompilationSession
subclass and handles all the RPC wrangling for you (#270). - Ports the LLVM service and example services to the new runtime (#277). This provides a net performance win with fewer lines of code.
Other highlights of this release include:
- [Core API] Adds a new
compiler_gym.wrappers
module that makes it easy to apply modular transformations to CompilerGym environments without modifying the environment code (#272). - [Core API] Adds a new
Datasets.random_benchmark()
method for selecting a uniform random benchmark from one or more datasets (#247). - [Core API] Adds a new
compiler_gym.make()
function, equivalent togym.make()
(#257). - [LLVM] Adds a new
IrSha1
observation space that uses a fast, service-side C++ implementation to compute a checksum of the environment state (#267). - [LLVM] Adds 12 new C programs from the CHStone benchmark suite (#284).
- [LLVM] Adds the
anghabench-v1
dataset and deprecatedanghabench-v0
(#242). - Numerous bug fixes and improvements.
This release introduces some significant changes to the way that benchmarks are managed, introducing a new dataset API. This enabled us to add support for millions of new benchmarks and a more efficient implementation for the LLVM environment, but this will require some migrating of old code to the new interfaces (see "Migration Checklist" below). Some of the key changes of this release are:
- [Core API change] We have added a Python
Benchmark
class (#190). The
env.benchmark
attribute is now an instance of this class rather than a string (#222). - [Core behavior change] Environments will no longer select benchmarks
randomly. Now
env.reset()
will now always select the last-used benchmark, unless thebenchmark
argument is provided orenv.benchmark
has been set. If no benchmark is specified, a default is used. - [API deprecations] We have added a new
Dataset
class hierarchy
(#191,
#192). All
datasets are now available without needing to be downloaded first, and a new
Datasets
class can be used to iterate over them
(#200). We have
deprecated the old dataset management operations, the
compiler_gym.bin.datasets
script, and removed the--dataset
and--ls_benchmark
flags from the command line tools. - [RPC interface change] The
StartSession
RPC endpoint now accepts a list of initial observations to compute. This removes the need for an immediate call toStep
, reducing environment reset time by 15-21% (#189). - [LLVM] We have added several new datasets of benchmarks, including the Csmith and llvm-stress program generators (#207), a dataset of OpenCL kernels (#208), and a dataset of compilable C functions (#210). See the docs for an overview.
CompilerEnv
now takes an optionalLogger
instance at construction time for fine-grained control over logging output (#187).- [LLVM] The ModuleID and source_filename of LLVM-IR modules are now anonymized to prevent unintentional overfitting to benchmarks by name (#171).
- [docs] We have added a Feature Stability section to the documentation (#196).
- Numerous bug fixes and improvements.
Please use this checklist when updating code for the previous CompilerGym release:
- Review code that accesses the
env.benchmark
property and update toenv.benchmark.uri
if a string name is required. Setting this attribute by string (env.benchmark = "benchmark://a-v0/b"
) and comparison to string types (env.benchmark == "benchmark://a-v0/b"
) still work. - Review code that calls
env.reset()
without first setting a benchmark. Previously, callingenv.reset()
would select a random benchmark. Now,env.reset()
always selects the last used benchmark, or a predetermined default if none is specified. - Review code that relies on
env.benchmark
beingNone
to select benchmarks randomly. Now,env.benchmark
is always set to the previously used benchmark, or a predetermined default benchmark if none has been specified. Settingenv.benchmark = None
will raise an error. Select a benchmark randomly by sampling from theenv.datasets.benchmark_uris()
iterator. - Remove calls to
env.require_dataset()
and related operations. These are no longer required. - Remove accesses to
env.benchmarks
. An iterator over available benchmark URIs is now available atenv.datasets.benchmark_uris()
, but the list of URIs cannot be relied on to be fully enumerable (the LLVM environments have over 2^32 URIs). - Review code that accesses
env.observation_space
and update toenv.observation_space_spec
where necessary (#228). - Update compiler service implementations to support the updated RPC interface
by removing the deprecated
GetBenchmarks
RPC endpoint and replacing it withDataset
classes. See the example service for details. - [LLVM] Update references to the
poj104-v0
dataset topoj104-v1
. - [LLVM] Update references to the
cBench-v1
dataset tocbench-v1
.
This release introduces public leaderboards to track the performance of user-submitted algorithms on compiler optimization tasks.
- Added a new
compiler_gym.leaderboard
package which contains utilities for preparing leaderboard submissions (#161). - Added a LLVM instruction count leaderboard and seeded it with a random search baseline (#117).
- Added support for Python 3.9, extending the set of supported python versions to 3.6, 3.7, 3.8, and 3.9 (#160).
- [llvm] Added a new
InstCount
observation space that contains the counts of each type of instruction (#159).
Build dependencies update notice: If you are building from source and
upgrading from an older version of CompilerGym, your build environment will need
to be updated. The easiest way to do that is to remove your existing conda
environment using conda remove --name compiler_gym --all
and to repeat the
steps in building from
source.
This release focuses on hardening the LLVM environments, providing improved semantics validation, and improving the datasets. Many thanks to @JD-at-work, @bwasti, and @mostafaelhoushi for code contributions.
- [llvm] Added a new
cBench-v1
dataset which changes the function attributes of the IR to permit inlining.cBench-v0
is deprecated and will be removed no earlier than v0.1.6. - [llvm] Removed 15 passes from the LLVM action space:
-bounds-checking
,-chr
,-extract-blocks
,-gvn-sink
,-loop-extract-single
,-loop-extract
,-objc-arc-apelim
,-objc-arc-contract
,-objc-arc-expand
,-objc-arc
,-place-safepoints
,-rewrite-symbols
,-strip-dead-debug-info
,-strip-nonlinetable-debuginfo
,-structurizecfg
. Passes are removed if they are: irrelevant (e.g. used only debugging), if they change the program semantics (e.g. inserting runtimes bound checking), or if they have been found to have nondeterministic behavior between runs. - Extended
env.step()
so that it can take a list of actions that are all performed in a single batch. This improve efficiency. - Added default reward spaces for
CompilerEnv
that are derived from scalar observations (thanks @bwasti!) - Added a new Q learning example (thanks @JD-at-work!).
- Deprecation: The v0.1.8 release will introduce a new datasets API that is
easier to use and more flexible. In preparation for this, the
Dataset
class has been renamed toLegacyDataset
, the following dataset operations have been marked deprecated:activate()
,deactivate()
, anddelete()
. TheGetBenchmarks()
RPC interface method has also been marked deprecated. - [llvm] Improved semantics validation using LLVM's memory, thread, address, and undefined behavior sanitizers.
- Numerous bug fixes and improvements.
This release adds numerous enhancements aimed at improving ease-of-use. Thanks to @broune, @hughleat, and @JD-ETH for contributions.
- Added a new
env.validate()
API for validating the state of an environment. Added semantics validation for some LLVM benchmarks. - Added a
env.fork()
method to efficiently duplicate an environment state. - The
manual_env
environment has been improved with new features such as hill climbing search and tab completion. - Ease of use improvements for string observation space and reward space names:
Added new getter methods such as
env.observation.Autophase()
and generated constants such asllvm.observation_spaces.autophase
. - Breaking change: Calculation of environment reward has been moved to Python. Reward functions have been removed from backend service implementations and replaced with equivalent Python classes.
- Various bug fixes and improvements.
- Add a new
compiler_gym.views.ObservationView.add_derived_space(...)
API for constructing derived observation spaces. - Added default reward and observation values for
env.step()
in case of service failure. - Extended the public
compiler_gym.datasets
API for managing datasets. - [llvm] Adds
-Norm
-suffixed rewards that are normalized to unoptimized cost. - Extended documentation and example codes.
- Numerous bug fixes and improvements.
- Expose the package version through
compiler_gym.__version__
, and the compiler version throughCompilerEnv.compiler_version
. - Add a notebook version of the "Getting Started" guide that can be run in colab.
- [llvm] Reformulate reward signals to be cumulative.
- [llvm] Add a new reward signal based on the size of the
.text
section of compiled object files. - [llvm] Add a
LlvmEnv.make_benchmark()
API for easily constructing custom benchmarks for use in environments. - Numerous bug fixes and improvements.
Initial release.