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# Mu Reference Implementation version 2
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[![Build Status](https://travis-ci.org/microvm/microvm-refimpl2.svg?branch=master)](https://travis-ci.org/microvm/microvm-refimpl2)

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Version 2.2.0
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This project is the current reference implementation of Mu, the micro virtual
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machine designed by [The Micro Virtual Machine Project](http://microvm.org).
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Version 2.2.0 implements the current [Mu
Specification](https://gitlab.anu.edu.au/mu/mu-spec).
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## How to compile
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**For the impatient**:

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* Install JDK 8. If you use Mac, download from
  [Oracle](http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html).
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* If you use Mac, install [Homebrew](http://brew.sh/).
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* Install [Scala](http://scala-lang.org/) 2.12. If you use Mac and Homebrew,
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  `brew install scala`.
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* Install [sbt](http://www.scala-sbt.org/) 1.0. If you use Mac and Homebrew,
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  `brew install sbt`.
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* Install [Scala IDE](http://scala-ide.org/) 4.6 or later (Eclipse with
  pre-installed plugins for Scala).
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* Clone this repository:

```bash
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git clone git@gitlab.anu.edu.au:mu/mu-impl-ref2.git
```

If you do not have SSH access to the ANU GitLab repositories, use the HTTPS URL:

```bash
git clone https://gitlab.anu.edu.au/mu/mu-impl-ref2.git
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```

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* In the directory `mu-impl-ref2`, do the following:
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```bash
sbt update genSrc
```

Then edit the project using your favourite IDE (or text editor).

* There is a [bug in the sbt-eclipse
  plugin](https://github.com/typesafehub/sbteclipse/issues/346) that prevents us
  form using it with SBT 1.0.0, therefore we cannot generate Eclipse project.
  Other IDEs, such as IntelliJ IDEA, should not be affected.

<!--
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```bash
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sbt update genSrc eclipse
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```

* Open Scala IDE and import the generated project as "existing project into
  workspace".
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-->
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**Detailed guide**:

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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.

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You also need [Scala](http://scala-lang.org/) 2.12 and
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[sbt](http://www.scala-sbt.org/) 1.0. It is recommended to install them using
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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](http://www.scala-sbt.org/download.html) from the official sbt web
site, or follow the [official sbt installing guide for
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Linux](http://www.scala-sbt.org/1.x/docs/Installing-sbt-on-Linux.html).  If
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you experience any "certificate" problems, [this
page](https://github.com/sbt/sbt/issues/2295) provides a solution.
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Then after cloning this repository, you can simply invoke `sbt compile` to
compile this project. Or you can do it step by step:
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* To download all dependencies from the Maven central repository, invoke `sbt
  update`.

* To generate the Mu IR parser from the Antlr grammar, invoke `sbt genSrc`. The
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  generated sources will be in the `target/scala-2.12/src_managed` directory.
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* To compile, invoke `sbt compile`. This will also generate the Mu IR parser
  using Antlr.
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As mentioned before, a bug in [sbt-eclipse
plugin](https://github.com/typesafehub/sbteclipse) prevents us from using it on
Sbt 1.0. Let's wait for it to be fixed.

<!--
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To generate an Eclipse project, install the [sbt-eclipse
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plugin](https://github.com/typesafehub/sbteclipse) and invoke `sbt eclipse`.
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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.
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-->
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IntelliJ IDEA has plugins for Scala and SBT. Make sure you don't commit `.idea`
or generated project files into the repository.
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### C binding and Python binding

The C binding is in the `cbinding` directory. Just run `make` inside `cbinding`.

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.

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See [cbinding/README.md](cbinding/README.md) and
[pythonbinding/README.md](pythonbinding/README.md) for more details.
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## How to test

For the impatient: run the `test.sh` script.

Detailed steps:

1. Compile native programs necessary for testing the native interface:

```bash
pushd tests/c-snippets
make
popd
```

2. Set the `TRAVIS` environment variable to `true`:

```bash
export TRAVIS=true
```

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.

3. Run `sbt test`.

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## How to run
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For the impatient: Execute the following command and see Mu running a factorial
example.

```
sbt 'set fork:=true' 'test:runMain junks.FactorialFromRPython'
```

### C API

The reference implementation implements the [Mu Client
API](https://gitlab.anu.edu.au/mu/mu-spec/blob/master/api.rst) which allows C
programs to control the micro VM and construct and deliver bundles for the micro
VM to execute.

See [cbinding/README.md](cbinding/README.md) for more details.

### Scala API

The micro VM itself is implemented in Scala.

- `uvm.refimpl.MicroVM` is the counterpart of the `MuVM` struct in the [Mu
  Client API](https://gitlab.anu.edu.au/mu/mu-spec/blob/master/api.rst). It can
  be instantiated with VMConf options explained below.
- `uvm.refimpl.MuCtx` is the counterpart of the `MuCtx` struct in C.
- `uvm.refimpl.MuValue` and its subclasses implement the `MuValue` handles.

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
interface.

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There is a sample factorial program (generously provided by @johnjiabinzhang) in
the `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.

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### Boot Image

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 `.muref`.

Before a boot image can be executed, an entry point needs to be specified. Use
the `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 `uptr<uptr<int<8>>>` as
parameters, the same as the `main` function in C.

The `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.

The `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](cbinding/refimpl2-start.h) header provides the
`mu_refimpl_new_ex` function which accepts a C-style string. The options are
encoded as `key=value` pairs, one option per line, with no spaces between the
equal sign.

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.

Options:

*Sizes may have suffixes K, M, G or T. 1K = 1024 bytes. sosSize, losSize and
globalSize must be a multiple of 32768 bytes (32K).*

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- **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
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- **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
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  parsing!!!  Enable only if the bundle is small. default: false
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- **automagicReloc**: Allow "automagic" relocation.  If true, `uptr` and
  `ufuncptr` fields will also be traced during boot image building.  If a `uptr`
  field points to a global cell field, it will still point to the same field
  after boot image loading; if a `ufuncptr` points to a native function, it will
  point to the same function after boot image loading.  default: false
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- **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
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  `path` argument of the `dlopen` system 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.
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- **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](https://gitlab.anu.edu.au/mu/mu-client-pypy/) project to
  work. default: false
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Holstein uses the [logback](https://logback.qos.ch/) framework as its logging
backend.  Logs can be configured using XML configuration by specifying the
following option:

- **logbackConfig**: The path to the logback XML configuration file.

Example:

```
  ./tools/runmu.sh --logbackConfig=./logging/logging.xml -- ./target/boot-image-echo.muref Hello world!
```

Alternatively, you can set the log level using the following options.  *Log
levels can be: ALL, TRACE, DEBUG, INFO, WARN, ERROR, OFF. Case-insensitive.
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Setting to WARN should get rid of most logging information, except the serious
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ones.* The default log level is DEBUG.
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- **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.
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## Implementation details

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
is `uvm.refimpl.MicroVM`, which implements the `MuVM` struct specified by the
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[client API](https://gitlab.anu.edu.au/mu/mu-spec/blob/master/api.rst), but is
more Scala-like. The client interacts with the micro VM via `uvm.refimpl.MuCtx`
instances created by the `MicroVM` instance, which corresponds to the `MuCtx`
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.
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The client can also be written in C, Python or other languages that can
interface with C.
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### Threading model

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
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  [watchpoints](https://gitlab.anu.edu.au/mu/mu-spec/blob/master/instruction-set.rst#traps-and-watchpoints)
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  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:

```scala
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.
```

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The refimpl implements the text-based IR and HAIL as well as the IR-builder API
to construct Mu IR ASTs programmatically. 
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### Garbage collection

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.

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- `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<int<32> 4>`, `vec<float 4>` and
  `vec<double 2>` can be loaded or stored from the memory.
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- The tagged reference type `tagref64` is fully implemented.

- Out-of-memory errors will terminate the VM rather than letting the Mu IR
  handle such failures via the exception clauses.

### Native interface

This reference implementation assumes it is running on x86-64 on either Linux or
OSX. It implements the [AMD64 Unix Native
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Interface](https://gitlab.anu.edu.au/mu/mu-spec/blob/master/native-interface-x64-unix.rst)
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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
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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 `LICENSE`.

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## Contact
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Kunshan Wang <kunshan.wang@anu.edu.au>

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