Skip to content

Latest commit

 

History

History
85 lines (60 loc) · 3.67 KB

README.md

File metadata and controls

85 lines (60 loc) · 3.67 KB
Raw

AllocCheck.jl

AllocCheck.jl is a Julia package that statically checks if a function call may allocate by analyzing the generated LLVM IR of it and its callees using LLVM.jl and GPUCompiler.jl

AllocCheck operates on functions, attempting to determine statically whether a function may allocate memory, and if so, where that allocation appears. This is different from measuring allocations using, e.g., @time or @allocated, which measures the allocations that actually happened during the execution of a function.

Getting started

The primary entry point to check allocations is the macro @check_allocs which is used to annotate a function definition that you'd like to enforce allocation checks for:

julia> using AllocCheck

julia> @check_allocs multiply(x, y) = x * y
multiply (generic function with 1 method)

julia> multiply(1.5, 2.5) # call automatically checked for allocations
3.75

julia> multiply(rand(3, 3), rand(3, 3)) # result matrix requires an allocation
ERROR: @check_allocs function encountered 1 errors (1 allocations / 0 dynamic dispatches).

The multiply(::Float64, ::Float64) call happened without error, indicating that the function was proven not to allocate. On the other hand, the multiply(::Matrix{Float64}, ::Matrix{Float64}) call raised an AllocCheckFailure due to one internal allocation.

The errors field can be used to inspect the individual errors:

julia> try
           multiply(rand(3, 3), rand(3, 3))
       catch err
           err.errors[1]
       end
Allocation of Matrix{Float64} in ./boot.jl:477
  | Array{T,2}(::UndefInitializer, m::Int, n::Int) where {T} =

Stacktrace:
 [1] Array
   @ ./boot.jl:477 [inlined]
 [2] Array
   @ ./boot.jl:485 [inlined]
 [3] similar
   @ ./array.jl:418 [inlined]
 [4] *(A::Matrix{Float64}, B::Matrix{Float64})
   @ LinearAlgebra ~/.julia/juliaup/julia-1.10.0-rc1+0.x64.linux.gnu/share/julia/stdlib/v1.10/LinearAlgebra/src/matmul.jl:113
 [5] var"##multiply#235"(x::Matrix{Float64}, y::Matrix{Float64})
   @ Main ./REPL[13]:1

Functions that throw exceptions

Some functions that we do not expect may allocate memory, like sin, actually may:

julia> @allocated try
           sin(Inf)
       catch
       end
48

The reason for this is that sin needs to allocate if it throws an error.

By default, @check_allocs ignores all such allocations and assumes that no exceptions are thrown. If you care about detecting these allocations anyway, you can use ignore_throw=false:

julia> @check_allocs mysin1(x) = sin(x)

julia> @check_allocs ignore_throw = false mysin2(x) = sin(x)

julia> mysin1(1.5)
0.9974949866040544

julia> mysin2(1.5)
ERROR: @check_allocs function encountered 2 errors (1 allocations / 1 dynamic dispatches).

Limitations

Every call into a @check_allocs function behaves like a dynamic dispatch. This means that it can trigger compilation dynamically (involving lots of allocation), and even when the function has already been compiled, a small amount of allocation is still expected on the function entry.

For most applications, the solution is to use @check_allocs to wrap your top-level entry point or your main application loop, in which case those allocations are only incurred once. @check_allocs will guarantee that no dynamic compilation or allocation occurs once your function has started running.