enso/docs/runtime/ir-caching.md
Hubert Plociniczak 6769ab0ee7
Downgrade hashing to SHA-1 and other optimizations (#5791)
This change downgrades hashing algorithm used in caching IR and library bindings to SHA-1. It is sufficient and significantly faster for the purpose of simple checksum we use it for.

Additionally, don't calculate the digest for serialized bytes - if we get the expected object type then we are confident about the integrity.

Don't initialize Jackson's ObjectMapper for every metadata serialization/de-serialization. Initialization is very costly.

Avoid unnecessary conversions between Scala and Java. Those back-and-forth `asScala` and `asJava` are pretty expensive.

Finally fix an SBT warning when generating library cache.

Closes https://github.com/enso-org/enso/issues/5763

# Important Notes
The change cuts roughly 0.8-1s from the overall startup.
This change will certainly lead to invalidation of existing caches. It is advised to simply start with a clean slate.
2023-03-09 07:36:59 +00:00

12 KiB

layout title category tags order
developer-doc IR Caching in the Enso Compiler runtime
runtime
caching
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IR Caching in the Enso Compiler

One of the largest pain points for users of Enso at the moment is the fact that it has to precompile the entire standard library on every project load. This is, in essence, due to the fact that the current parser is abysmally slow, and incredibly demanding. The obvious solution to improve this is to take the parser out of the equation in its entirety, by serialising the parser's output.

To that end, we want to serialise the Enso IR to a format that can later be read back in, bypassing the parser entirely. Furthermore, we can move the boundary at which this serialisation takes place to the end of the compiler pipeline, thereby bypassing doing most of the compilation work, and further improving startup performance.

Serialising the IR

As the serialised IR doesn't need to be read by anything other than Enso, we need not use a representation that is portable between platforms. As a result, we have picked the Serializable infrastructure that is already present on the JVM. It has the following benefits:

  • It is able to serialise arbitrary object graphs while maintaining object identity and tracking references. This cannot be disabled for Serializable, but that is fine as we want it.
  • It is built into the JVM and is hence guaranteed to be portable between instances of the same JVM.
  • It copes fine with highly-nested scala types, like our IR.

In order to maximise the benefits of this process, we want to serialise the IR as late in the compiler pipeline as possible. This means serialising it just before the code generation step that generates Truffle nodes (before the RuntimeStubsGenerator and IrToTruffle run).

This serialisation should take place in an offloaded thread so that it doesn't block the compiler from continuing.

Doing this naïvely, however, means that we can inadvertently end up serialising the entire module graph. This is due to the BindingsMap, which contains a reference to the associated runtime.Module, from which there is a reference to the ModuleScope. The ModuleScope may then reference other runtime.Modules which all contain IR.Modules. Therefore, done in a silly fashion, we end up serialising the entire reachable module graph. This is not what we want.

While the ideal way of solving this problem would be to customise the serialisation and deserialisation process for the BindingsMap, the JVM's Serializable does not provide the ability to customise it enough to solve this problem. Instead, we solve it using a preprocessing step:

  • We can modify BindingsMap and its child types to be able to contain an unlinked module pointer case class ModulePointer(qualifiedName: List[String]) in place of a Module.
  • As the MetadataStorage type that holds the BindingsMap is mutable it can be updated in place without having to reassemble the entire IR graph.
  • Hence, we can traverse all the nodes in the ir.preorder that have metadata consisting of either the BindingsMap or ResolvedName types (provided by the following passes: BindingAnalysis, MethodDefinitions, GlobalNames, VectorLiterals, Patterns), and perform a replacement.

Having done this, we have broken any links that the IR may hold between modules, and can serialise each module individually.

This serialisation must take place after codegen has happened as it modifies the IR in place. The compiler can handle giving it to the offloaded serialisation thread. It may be necessary to duplicate the IR before handing it to this thread, but this should be checked during development.

Storing the IR

The serialized IR needs to be stored in a location that is tied to the library that it serializes. Despite this, we also want to be able to ship cached IR with libraries. This leads to a two pronged solution where we check two locations for the cache.

  1. With the Library: As libraries can have a hidden .enso directory, we can use a path within that for caching. This should be $package/.enso/cache/ir/enso-$version/, and can be accessed by extending the pkg library to be aware of the cache directories.
  2. Globally: As some library locations may not be writeable, we need to have a global out-of-line cache that is used if the first one is not writeable. This is located under $ENSO_DATA (whose location can be obtained from the RuntimeDistributionManager), and is located under the path $ENSO_DATA/cache/ir/$hash/enso-$version/, where $hash is the SHA3-224 hash of the tuple (namespace, library_name, version), where version = SemVer | "local". This hash is computed by concatenating the string representations of these fields.

In each location, the IR is stored with the following assumptions:

  • The IR file is located in a directory modelled after its module path, followed by a file named after the module itself with the extension .ir (e.g. the IR for Standard.Base.Data.Vector is stored in Standard/Base/Data/Vector.ir).
  • The metadata file is located in a directory modelled after its module path, followed by a file named after the module itself with the extension .meta (e.g. the metadata for Standard.Base.Data.Vector.enso is stored in Standard/Base/Data/Vector.meta). This is right next to the corresponding .ir file.

Storage of the IR only takes place iff the intended location for that IR is empty.

Metadata Format

The metadata is used for integrity checking of the cached IR to prevent loading corrupted or out of date data from the cache. Due to the fact that engines can only load IR created by their versions, and cached IR is located in a directory named after the engine version, this format need not be forward compatible.

It is a JSON file as follows:

{
  sourceHash: String; // The hash of the corresponding source file.
  blobHash: String; // The hash of the blob.
  compilationStage: String; // The compilation stage of the IR.
}

All hashes are encoded in SHA1 format, for performance reasons. The engine version is encoded in the cache path, and hence does not need to be explicitly specified in the metadata.

Portability Guarantees

As part of this design we provide only the following portability guarantees:

  • The serialised IR must be able to be deserialised by the same version of Enso that wrote the original blob.

Loading the IR

Loading the IR is a multi-stage process that involves performing integrity checking on the loaded cache. It works as follows.

  1. Find the Cache: Look in the global cache directory under $ENSO_DATA. If there is no cached IR here that is valid for the current configuration, check the ibrary's .enso/cache folder. This should be hooked into in Compiler::parseModule.
  2. Check Integrity: Check the module's metadata for validity according to the integrity rules.
  3. Load: If the cache passes the integrity check, load the .ir file. If deserialisation fails in any way, immediately fall back to parsing the source file.
  4. Re-Link: If loading completed successfully, re-link the BindingsMap metadata to the proper modules in question.

The main subtlety here is handling the dependencies between modules. We need to ensure that, when loading multiple cached libraries, we properly handle them one-by-one. Doing this is as simple as hooking into Compiler::parseModule and setting AFTER_STATIC_PASSES as the compilation state after loading the module. This will tie into the current ImportsResolver and ExportsResolver which are run in an un-gated fashion in Compiler::run.

In order to prevent the execution of malicious code when deserialising we should employ a deserialisation filter as built into the JDK.

Integrity Checking

For a cache to be usable, the following properties need to be satisfied:

  1. The sourceHash must match the hash of the corresponding source file.
  2. The blobHash must match the hash of the corresponding .ir file.

If any of these fail, the cache file should be deleted where possible, or ignored if it is in a read-only location.

Error Handling

It is important, as part of this, that we fail under all circumstances into a working state. This means that:

  • If serialisation fails, we report a low-priority error message and continue.
  • If deserialisation fails, we fall back to loading and parsing the original source file.

At no point should this mechanism be exposed to the user in any visible way, other than the fact that they may be seeing the actual files on disk.

Imports

Integrity Checking does not check the situation when the cached module imports a module which cache has been invalidated. For example, module A uses a method foo from module B and a successful compilation resulted in IR cache for both A and B. Later, someone modified module B by renaming method foo to bar. If we only compared source hashes, B's IR would be re-generated while A's would be loaded from cache, thus failing to notice method name change, until a complete cache invalidation was forced.

Therefore, the compiler performs an additional check by invalidating module's cache if any of its imported modules have been invalidated.

Testing the Serialisation

There are two main elements that need to be tested as part of this feature.

  • Firstly, we need to test the serialisation and deserialisation process, including the rewrite of BindingsMap to work properly.
  • We also need to test the discovery of cache locations on the filesystem and cache eviction strategies. The best way to do this is to set $ENSO_DATA to a temporary directory and then directly interact with the filesystem. Caching should be disabled for existing tests. This will require adding additional runtime options for debugging, but also constructing the DistributionManager on context creation (removing RuntimeDistributionManager).

Import/Export caching of bindings

Import and export resolution is one of the more expensive elements in the initial pipeline. It is also the element which does not change for the releases library components as we do not expect users to modify them. During the initial compilation stage we iteratively parse/load cached ir, do import resolution on the module, followed by export resolution, and repeat the process with any dependent modules discovered in the process. Calculating such transitive closure is an expensive and repeatable process. By caching bindings per library we are able to skip that process completely and discover all necessary modules of the library in a single pass.

The bindings are serialized along with the library caches in a file with a .bindings suffix.

Future Directions

Due to the less than ideal platform situation we're in, we're limited to using Java's Serializable. It is not as performant as other options.

  • FST is around 10x faster than the JVM's serialization, and is a drop-in replacement.
  • However, the version that supports Java 11 utilises reflection that trips warnings that will be disallowed with Java 17 (the next LTS version for GraalVM).
  • The version that fixes this relies on the foreign memory API which is available in Java 17. I recommend that once we're on Java 17 builds the serialization is updated to work using FST.