Mjolnir.jl

A little less conversation, a little more abstraction
Popularity
87 Stars
Updated Last
10 Months Ago
Started In
March 2020

⚠️ This project was experimental and is not currently maintained. It may be picked up at some point in the future, but for now it is both incomplete and likely non-functional on newer versions of Julia. For a discussion of why development has not continued, see this thread.

Mjolnir

Build Status ColPrac: Contributor's Guide on Collaborative Practices for Community Packages

Mjolnir is a hybrid approach to partial evaluation / abstract interpretation, with an implementation in Julia. It can be thought of as a blend of operator-overloading based tracing (as in JAX, PyTorch Script, staged programming systems etc.) and dataflow-based abstract interpretation (as in the type inference systems of Julia, TypeScript and Crystal). It is aimed at package developers rather than Julia end-users.

Mjolnir can reproduce the compact, linear traces (aka computation graphs or Wengert lists) of tracing systems.

julia> function pow(x, n)
         r = 1
         while n > 0
           n -= 1
           r *= x
         end
         return r
       end
pow (generic function with 1 method)

julia> using Mjolnir

julia> @trace pow(::Int, 3)
1: (%1 :: const(pow), %2 :: Int64, %3 :: const(3))
  %4 = (*)(1, %2) :: Int64
  %5 = (*)(%4, %2) :: Int64
  %6 = (*)(%5, %2) :: Int64
  return %6

However, it avoids several of the downsides of those systems. It supports arbitrary Julia types (not just 'tensors' but also strings and structs). It supports value-dependent control flow (as it can encode branches in the trace). It supports side effects and mutating operators. Functions like println don't have to be evaluated at compile time. It can enforce its assumptions (i.e. referential transparency) rather than making the user responsible for them, and can generate diagnostics when there are issues. Mjolnir can thus compile a much wider range of Julia programs than OO approaches.

julia> @trace pow(::Int, ::Int)
1: (%1 :: const(pow), %2 :: Int64, %3 :: Int64)
  %4 = (>)(%3, 0) :: Bool
  br 3 (1) unless %4
  br 2 (%3, 1)
2: (%5 :: Int64, %6 :: Int64)
  %7 = (-)(%5, 1) :: Int64
  %8 = (*)(%6, %2) :: Int64
  %9 = (>)(%7, 0) :: Bool
  br 3 (%8) unless %9
  br 2 (%7, %8)
3: (%10 :: Int64)
  return %10
julia> function pow(x, n)
         r = 1
         while n > 0
           n -= 1
           r *= x
           @show r
         end
         return r
       end
pow (generic function with 1 method)

julia> @trace pow(2, 3)
1: (%1 :: const(pow), %2 :: const(2), %3 :: const(3))
  %4 = (println)("r = ", "2") :: Nothing
  %5 = (println)("r = ", "4") :: Nothing
  %6 = (println)("r = ", "8") :: Nothing
  return 8

Mjolnir is designed to be highly customisable, and to give as much control as possible to packages that build on it.

Required Packages

Used By Packages