Debugging

One of the most challenging tasks that users have is: debug a large simulation that is breaking, e.g., yielding NaNs somewhere. This is especially complex for large models with many terms and implicit time-stepping with all the bells and whistles that the CliMA ecosystem offers.

ClimaCore has a module, ClimaCore.DebugOnly, which contains tools for debugging simulations for these complicated situations.

Because so much data (for example, the solution state, and many cached fields) is typically contained in ClimaCore data structures, we offer a hook to inspect this data after any operation that ClimaCore performs.

Example

Print NaNs when they are found

In this example, we add a callback that simply prints NaNs found every instance when they are detected in a ClimaCore operation.

To do this, we need two ingredients:

First, we need to enable the callback system:

import ClimaCore
ClimaCore.DebugOnly.call_post_op_callback() = true

The line ClimaCore.DebugOnly.call_post_op_callback() = true means that at the end of every ClimaCore operation, the function ClimaCore.DebugOnly.post_op_callback is called. By default, this function does nothing. So, the second ingredient is to define a method:

function ClimaCore.DebugOnly.post_op_callback(result, args...; kwargs...)
    if any(isnan, parent(result))
        println("NaNs found!")
    end
end

If needed, post_op_callback can be specialized or behave differently in different cases, but here, it only checks if NaNs are in the given that.

Note that, due to dispatch, post_op_callback will likely need a very general method signature, and using post_op_callback (result::DataLayouts.VIJFH, args...; kwargs...) above fails (on the CPU), because post_op_callback ends up getting called multiple times with different datalayouts.

Now, let us put everything together and demonstrate a complete example:

import ClimaCore
ClimaCore.DebugOnly.call_post_op_callback() = true
function ClimaCore.DebugOnly.post_op_callback(result, args...; kwargs...)
    if any(isnan, parent(result))
        println("NaNs found!")
    end
end

FT = Float64
data = ClimaCore.DataLayouts.VIJFH{FT}(Array{FT}, zeros; Nv=5, Nij=2, Nh=2)
@. data = NaN

NaNs found!
NaNs found!
NaNs found!
NaNs found!
NaNs found!
NaNs found!
NaNs found!
NaNs found!
NaNs found!
NaNs found!
NaNs found!
NaNs found!
NaNs found!

This example should print NaN on your standard output.

Infiltrating

Infiltrator.jl is a simple debugging tool for Julia packages.

Here is an example, where we can use Infiltrator.jl to find where NaNs is coming from interactively.

import ClimaCore
import Infiltrator # must be in your default environment
ClimaCore.DebugOnly.call_post_op_callback() = true
function ClimaCore.DebugOnly.post_op_callback(result, args...; kwargs...)
    has_nans = any(isnan, parent(result))
    has_inf = any(isinf, parent(result))
    if has_nans || has_inf
        has_nans && println("NaNs found!")
        has_inf && println("Infs found!")
        # Let's define the stack trace so that we know where this came from
        st = stacktrace()

        # Let's use Infiltrator.jl to exfiltrate to drop into the REPL.
        # Now, `Infiltrator.safehouse` will be a NamedTuple
        # containing `result`, `args`, `kwargs` and `st`.
        Infiltrator.@exfiltrate
        # sometimes code execution doesn't stop, I'm not sure why. Let's
        # make sure we exfiltrate immediately with the data we want.
        error("Exfiltrating.")
    end
end

FT = Float64
data = ClimaCore.DataLayouts.VIJFH{FT}(Array{FT}, zeros; Nv=5, Nij=2, Nh=2)
@. data = NaN
# Let's see what happened
(;result, args, kwargs, st) = Infiltrator.safehouse;

# You can print the stack trace, to see where the NaNs were found:
ClimaCore.DebugOnly.print_depth_limited_stack_trace(st; maxtypedepth=1)

# Once there, you can see that the call lead you to `copyto!`,
# Inspecting `args` shows that the `Broadcasted` object used to populate the
# result was:
julia> args[2]
Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{0}}(identity, (NaN,))

# And there's your problem, NaNs is on the right-hand-side of that assignment.

Caveats