Mu Reference Implementation version 2
This project is the current reference implementation of Mu, the micro virtual machine designed by The Micro Virtual Machine Project.
Version 2.2.0 implements the current Mu Specification.
How to compile
For the impatient:
- Install JDK 8. If you use Mac, download from Oracle.
- If you use Mac, install Homebrew.
- Install Scala 2.12. If you use Mac and Homebrew,
brew install scala.
- Install sbt 0.13. If you use Mac and Homebrew,
brew install sbt.
- Install Scala IDE 4.6 or later (Eclipse with pre-installed plugins for Scala).
- Clone this repository:
git clone email@example.com:mu/mu-impl-ref2.git
If you do not have SSH access to the ANU GitLab repositories, use the HTTPS URL:
git clone https://gitlab.anu.edu.au/mu/mu-impl-ref2.git
- In the directory
mu-impl-ref2, do the following:
sbt update genSrc eclipse
- Open Scala IDE and import the generated project as "existing project into workspace".
The reference implementation is developed and tested with Java VM 8. You need a JRE to build the Scala/Java part, and a JDK to build the C binding.
You also need Scala 2.12 and sbt 0.13. It is recommended to install them using the package manager of your operating system or distribution (such as apt-get, yum, pacman, etc. for GNU/Linux distributions and Homebrew for Mac OS X) if such packages are available.
For Ubuntu users: Ubuntu 15.10 does not provide sbt in its repository. Please download sbt from the official sbt web site, or follow the official sbt installing guide for Linux. If you experience any "certificate" problems, this page provides a solution.
Then after cloning this repository, you can simply invoke
sbt compile to
compile this project. Or you can do it step by step:
To download all dependencies from the Maven central repository, invoke
To generate the Mu IR parser from the Antlr grammar, invoke
sbt genSrc. The generated sources will be in the
To compile, invoke
sbt compile. This will also generate the Mu IR parser using Antlr.
To generate an Eclipse project, install the sbt-eclipse
plugin and invoke
Make sure you generate the parser (
sbt genSrc) before creating the Eclipse
project, so that the generated sources will be on the Eclipse build path.
IntelliJ IDEA has plugins for Scala and SBT. Make sure you don't commit
or generated project files into the repository.
C binding and Python binding
The C binding is in the
cbinding directory. Just run
The Python binding is in the
pythonbinding directory. It depends on the C
binding, so make sure you make the C binding first. The Python binding does not
need to be built.
How to test
For the impatient: run the
- Compile native programs necessary for testing the native interface:
pushd tests/c-snippets make popd
- Set the
TRAVISenvironment variable to
This will tell the test cases in
src/test/scala not to print excessive logs
which would be helpful for identifying problems for individual test cases.
How to run
For the impatient: Execute the following command and see Mu running a factorial example.
sbt 'set fork:=true' 'test:runMain junks.FactorialFromRPython'
The reference implementation implements the Mu Client API which allows C programs to control the micro VM and construct and deliver bundles for the micro VM to execute.
See cbinding/README.md for more details.
The micro VM itself is implemented in Scala.
uvm.refimpl.MicroVMis the counterpart of the
MuVMstruct in the Mu Client API. It can be instantiated with VMConf options explained below.
uvm.refimpl.MuCtxis the counterpart of the
MuCtxstruct in C.
uvm.refimpl.MuValueand its subclasses implement the
As an implementation detail, the micro VM will not start execution until
MicroVM.execute() is called. See implementation details below.
The Scala interface is closer to the Scala's style. For example, the
MuCtx.dumpKeepalives() method returns a
Seq[MuValue] rather than writing the
results into a given array. It also does more static type checking than the C
There is a sample factorial program (generously provided by @johnjiabinzhang) in
src/test directory. To run the program with all dependencies on the
classpath, you need to run it with sbt. Invoke
sbt to enter the interactive
shell. Then type:
set fork := true test:runMain junks.FactorialFromRPython
or directly from the command line:
sbt 'set fork:=true' 'test:runMain junks.FactorialFromRPython'
fork := true tells sbt to run the program in a different process than the one
running sbt itself.
The reference implementation can create boot images, a package that contains a Mu IR bundle and a serialised Mu memory, including the global memory and the heap.
Boot images can be created using the standard
make_boot_image method on the
MuVM object. In this reference implementation, the boot image is a zip file. By
convention, boot images have the file-name extension
Before a boot image can be executed, an entry point needs to be specified. Use
tools/mar.py script to set the entry point by ID or name. The entry point
is a Mu function that takes an
int<32> and a
parameters, the same as the
main function in C.
tools/mar.py script can also specify extra libraries to be loaded when the
micro VM loads the boot image. EXTERN constants will be resolved from these
libraries in the order of those libraries.
tools/runmu.sh script runs the micro VM with the given boot image.
Additional arguments are passed to the entry point.
Micro VM Configuration
There are some parameters that controls the behaviour of the reference implementation.
When using the C API, the refimpl-specific
cbinding/refimpl2-start.h header provides the
mu_refimpl_new_ex function which accepts a C-style string. The options are
key=value pairs, one option per line, with no spaces between the
When using the
tools/runmu.sh script, the options are specified as
command-line options in the form
--key=value before the boot image file name.
Sizes may have suffixes K, M, G or T. 1K = 1024 bytes. sosSize, losSize and globalSize must be a multiple of 32768 bytes (32K).
- sosSize: The size of the small object space in bytes. default: 2M
- losSize: The size of the large object space in bytes. default: 2M
- globalSize: The size of the large object space in bytes. default: 1M
- stackSize: The size of each stack in bytes. default: 60K
- dumpBundle: Print out the bundle as text every time a bundle is loaded. default: false
- staticCheck: Run static checker after each bundle is loaded. default: true
- sourceInfo: Provide line/column info in Mu IR when errors occur. May be useful for debugging small Mu IR bundles, but will significantly slow down parsing!!! Enable only if the bundle is small. default: false
automagicReloc: Allow "automagic" relocation. If true,
ufuncptrfields will also be traced during boot image building. If a
uptrfield points to a global cell field, it will still point to the same field after boot image loading; if a
ufuncptrpoints to a native function, it will point to the same function after boot image loading. default: false
extraLibs: Extra libraries to load when starting the micro VM. This is a
colon-separated list of libraries. Each library has the same syntax of the
pathargument of the
dlopensystem function. By default, it does not load any extra libraries.
- bootImg: The path to the boot image. Only useful in the C API. By default, it does not load any boot image.
uPtrHack: When true, it will allow memory locations of general reference
types to be accessed by
uptr<T>. By default, such fields can only be accessed by
iref<T>, but this hack is necessary for the current mu-client-pypy project to work. default: false
Log levels can be: ALL, TRACE, DEBUG, INFO, WARN, ERROR, OFF. Case-insensitive. Setting to WARN should get rid of most logging information, except the serious ones. The default log level is DEBUG.
- vmLog: The log level of the micro VM (the "uvm" package)
- gcLog: The log level of the garbage collector (the "uvm.refimpl.mem" package). If vmLog is set but gcLog is not, it will use the log level of vmLog.
This reference implementation aims to be easy to work with, but does not have high performance. It may be used by client writers to evaluate the Mu micro VM, and may also be used by Mu micro VM implementers as a reference to compare with.
The micro VM is implemented as an interpreter written in Scala. The main class
uvm.refimpl.MicroVM, which implements the
MuVM struct specified by the
client API, but is
more Scala-like. The client interacts with the micro VM via
instances created by the
MicroVM instance, which corresponds to the
struct in the spec.
uvm.refimpl.MuValue and its subclasses implement the
MuValue handles, but has a real Scala type hierarchy and does extra type
checking when converting, which is not required by the spec.
The client can also be written in C, Python or other languages that can interface with C.
It uses green threads to execute multiple Mu threads and uses a round-robin scheduler: the interpreter iterates over all active threads, executes one instruction for each active thread, then repeat this process. However, the whole Scala-based program itself is not thread safe. Do not run multiple JVM or native threads. This means, you can still experiment with concurrent Mu programs, but there are some corner cases that do not work in this refimpl. For example:
Waiting for other Mu threads in the trap handler. The trap handler is executed by the same thread executing the Mu IR. During trap handler, no Mu program is executed. So if you want to use watchpoints to wait for certain Mu thread to come to a certain rendezvous point (a common optimisation trick), you should either wait within Mu IR (not in trap handlers) or try the high-performance Mu implementation which is still being written.
Synchronising with concurrent native programs via pointers, atomic memory access and futex. This is the realistic way for Mu to synchronise with native programs or foreign languages, but this refimpl implements atomic memory access as not-atomic (since it uses green thread) and implements futex in Scala (since it has its own scheduler).
The MicroVM instance will not start executing unless its
execute() method is
called. This method is specific to this implementation, and is not defined in
the specification. This also means the client cannot run concurrently with the
MicroVM, i.e. once started, the client can only intervene in the execution in
trap handlers. So a common use pattern is:
val microVM = new MicroVM() val uir = myCompiler.compile(sourceCode) val ctx = microVM.newContext() ctx.loadBundle(uir) microVM.setTrapHandler(theTrapHandler) // Set the trap handler so the client // can talk with the VM when trapped. val stack = ctx.newStack(theMainFunction) val thread = ctx.newThread(stack, Seq(params, to, the, main, function)) microVM.execute() // The current JVM thread will run on behalf of the MicroVM. // This blocks until all Mu threads stop. // However, MicroVM will call theTrapHandler.
The refimpl implements the text-based IR and HAIL as well as the IR-builder API to construct Mu IR ASTs programmatically.
This reference implementation has an exact tracing garbage collector with a mark-region small object space and a mark-sweep large object space.
IR implementation-specific details
Many undefined behaviours in the specification will raise
UvmRuntimeException, such as division by zero, going below the last frame of a stack, accessing a NULL reference, etc. But this behaviour is not guaranteed.
int<n>for n = 1 to 128 are implemented.
vec<T n>is implemented for all T that are int, float or double, and all n >= 1. However, only 8, 16, 32, 64, 128-bit integers, float, double,
vec<double 2>can be loaded or stored from the memory.
The tagged reference type
tagref64is fully implemented.
Out-of-memory errors will terminate the VM rather than letting the Mu IR handle such failures via the exception clauses.
This reference implementation assumes it is running on x86-64 on either Linux or OSX. It implements the AMD64 Unix Native Interface of the specification. It can call native functions from Mu IR and let native programs call back to Mu IR.
It does not support throwing Mu exceptions into native programs, or handing C++-based exceptions.
Author and Copyright
This project is created by Kunshan Wang, Yi Lin, Steve Blackburn, Antony Hosking, Michael Norrish.
This project is released under the CC-BY-SA license. See
Kunshan Wang firstname.lastname@example.org