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feat: support sparse inline linear solves #117

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feat: support sparse inline linear solves #117

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13 changes: 12 additions & 1 deletion lib/ModelingToolkitTearing/src/ModelingToolkitTearing.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -118,11 +118,22 @@ function MTKBase.unhack_system(sys::System)
if sched isa MTKBase.Schedule
sched = copy(sched)
end
ics = MTKBase.get_initial_conditions(sys)
for (linsolve, idxs) in inline_linear_scc_map
A, b = @match linsolve begin
BSImpl.Term(; args) => args
end
A_mat = collect(A)::Matrix{SymbolicT}
A_mat = @match A begin
BSImpl.Term(; f, args) => if f === SU.Code.with_allocator
collect(A)::Matrix{SymbolicT}
elseif f === SparseArrays.SparseMatrixCSC
colptr = unwrap_const(ics[args[3]])::Vector{Int}
rowval = unwrap_const(ics[args[4]])::Vector{Int}
collect(SparseArrays.SparseMatrixCSC(unwrap_const(args[1])::Int, unwrap_const(args[2])::Int, colptr, rowval, collect(args[5])::Vector{SymbolicT}))::Matrix{SymbolicT}
else
@assert false
end
end
b_vec = collect(b)::Vector{SymbolicT}
N = length(b_vec)
x = Vector{SymbolicT}(undef, N)
Expand Down
101 changes: 73 additions & 28 deletions lib/ModelingToolkitTearing/src/reassemble.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -659,6 +659,7 @@ function get_linear_scc_linsol(state::TearingState, alg_eqs::Vector{Int},
A, b, eqs_mask, vars_mask = __reduce_linear_system!(A, b, var_eq_matching, alg_eqs, alg_vars)

N = length(b)
clil_A = A
A = collect(A)::Matrix{Num}

if N <= analytical_linear_scc_limit && _check_allow_symbolic_parameter(
Expand Down Expand Up @@ -704,45 +705,89 @@ function get_linear_scc_linsol(state::TearingState, alg_eqs::Vector{Int},
else
reference = fullvars[state_idx]
end
# Use the `ArrayMaker` form for `A` and `b`
A_regions = SU.RegionsT()
A_values = Symbolics.SArgsT()

# Reference for `DiffCache`
reference_args = Symbolics.SArgsT((reference, MTKBase.get_iv(sys)::SymbolicT))
inps = MTKBase.inputs(sys)
if !isempty(inps)
push!(reference_args, first(inps))
end
reference = Symbolics.STerm(
promote, reference_args;
type = Vector{Real}, shape = [1:length(reference_args)]
)[1]

A_sparsity = min(round(Int, 100 * count(SU._iszero ∘ unwrap, A) / length(A)), 99)
use_sparse_A = (A_sparsity == 97 && 80 <= N <= 120) ||
(A_sparsity == 98 && 150 <= N <= 250) || (A_sparsity == 99 && N >= 100)

@baggepinnen baggepinnen Jun 23, 2026 •
edited
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isn't it strange that the lower N-bound for use_sparse_A is 80, 150, 100 as sparsity increases?

@AayushSabharwal AayushSabharwal Jun 23, 2026

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Hmm, the 150 is an odd one out. I forgot why I did that 😅

if use_sparse_A
I = Int[]
J = Int[]
V = SymbolicT[]
nnz = sum(length, clil_A.row_cols)
sizehint!(I, nnz)
sizehint!(J, nnz)
sizehint!(V, nnz)
for i in eachindex(clil_A.row_cols)
rcol = clil_A.row_cols[i]
rval = clil_A.row_vals[i]
for (j, val) in zip(rcol, rval)
push!(I, i)
push!(J, j)
push!(V, unwrap(val))
end
end
spA = SparseArrays.sparse(I, J, V, N, N)
dump_linear_scc_to_file("large_scc_$(length(I)).jl", spA, vars[vars_mask])
sys, A_cache = MTKBase.add_diffcache(sys, length(spA.nzval))
sys, I_param = MTKBase.add_misc_parameter(sys, Int, 1:length(spA.colptr))
sys, J_param = MTKBase.add_misc_parameter(sys, Int, 1:length(spA.rowval))
ics = copy(MTKBase.get_initial_conditions(sys))
ics[I_param] = spA.colptr
ics[J_param] = spA.rowval
@set! sys.initial_conditions = ics
A_allocator = A_cache(reference)
nzval = SU.Code.with_allocator(A_allocator, Symbolics.SConst(spA.nzval))
A = Symbolics.STerm(
SparseArrays.SparseMatrixCSC,
Symbolics.SArgsT((spA.m, spA.n, I_param, J_param, nzval));
type = SparseArrays.SparseMatrixCSC{Real, Int}, shape = SU.ShapeVecT((1:N, 1:N))
)
else
# Use the `ArrayMaker` form for `A`
A_regions = SU.RegionsT()
A_values = Symbolics.SArgsT()
# fill the entire thing with zeros
push!(A_regions, SU.ShapeVecT((1:N, 1:N)))
push!(A_values, SU.Fill(A_regions[1])(Symbolics.COMMON_ZERO))

for i in axes(A, 1), j in axes(A, 2)
coeff = unwrap(A[i, j])
SU._iszero(coeff) && continue
push!(A_regions, SU.ShapeVecT((i:i, j:j)))
push!(A_values, Symbolics.SConst([coeff;;]))
end

A = SU.ArrayMaker{VartypeT}(
A_regions, A_values;
shape = SU.ShapeVecT((1:N, 1:N))
)
sys, A_cache = MTKBase.add_diffcache(sys, N * N)
A_allocator = A_cache(reference)
A = SU.Code.with_allocator(A_allocator, SU.Const{VartypeT}(A))
end

b_regions = SU.RegionsT()
b_values = Symbolics.SArgsT()
# fill the entire thing with zeros
push!(A_regions, SU.ShapeVecT((1:N, 1:N)))
push!(A_values, SU.Fill(A_regions[1])(Symbolics.COMMON_ZERO))
push!(b_regions, SU.ShapeVecT((1:N,)))
push!(b_values, SU.Fill(b_regions[1])(Symbolics.COMMON_ZERO))

for i in axes(A, 1), j in axes(A, 2)
coeff = unwrap(A[i, j])
SU._iszero(coeff) && continue
push!(A_regions, SU.ShapeVecT((i:i, j:j)))
push!(A_values, Symbolics.SConst([coeff;;]))
end

for (i, resid) in enumerate(b)
SU._iszero(resid) && continue
push!(b_regions, SU.ShapeVecT((i:i,)))
push!(b_values, Symbolics.SConst([resid]))
end

A = SU.ArrayMaker{VartypeT}(A_regions, A_values; shape = SU.ShapeVecT((1:N, 1:N)))
b = SU.ArrayMaker{VartypeT}(b_regions, b_values; shape = SU.ShapeVecT((1:N,)))

reference_args = Symbolics.SArgsT((reference, MTKBase.get_iv(sys)::SymbolicT))
inps = MTKBase.inputs(sys)
if !isempty(inps)
push!(reference_args, first(inps))
end
reference = Symbolics.STerm(
promote, reference_args;
type = Vector{Real}, shape = [1:length(reference_args)]
)[1]
sys, A_cache = MTKBase.add_diffcache(sys, N * N)
A_allocator = A_cache(reference)
A = SU.Code.with_allocator(A_allocator, SU.Const{VartypeT}(A))
sys, b_cache = MTKBase.add_diffcache(sys, N)
b_allocator = b_cache(reference)
b = SU.Code.with_allocator(b_allocator, SU.Const{VartypeT}(b))
Expand Down
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