# Possibility to store outcome of \`ForwardDiff.jacobian\` already in sparse format
**URL:** https://discourse.julialang.org/t/possibility-to-store-outcome-of-forwarddiff-jacobian-already-in-sparse-format/102635
**Category:** Numerics
**Tags:** forwarddiff, sparse
**Created:** [August 9, 2023, 12:22pm UTC](https://discourse.julialang.org/t/possibility-to-store-outcome-of-forwarddiff-jacobian-already-in-sparse-format/102635 "2023-08-09T12:22:06Z")
**Posts on this page:** 3
**Page:** 1
### Author:  [@DanDoe](https://discourse.julialang.org/u/DanDoe)
#### Post date: [August 9, 2023, 12:22pm UTC](https://discourse.julialang.org/t/possibility-to-store-outcome-of-forwarddiff-jacobian-already-in-sparse-format/102635/1 "2023-08-09T12:22:06Z")
I use `ForwardDiff.jacobian` in the following way:
```julia
function _jacobian_ad_forward(p, t0, u0_ode, du_ode, config)
J = ForwardDiff.jacobian(du_ode, u0_ode, config) do du_ode, u_ode
f!(du_ode, u_ode, p, t0)
end
return J
end
```
where my Jacobian `J` is typically very sparse.
I am aware of [SparseDiffTools.jl](https://github.com/JuliaDiff/SparseDiffTools.jl#sparsedifftoolsjl) which offers a sparse Jacobian computation based on a to-be-supplied sparsity pattern.
To my understanding `SparseDiffTools.jl` does computations then only for the non-zero entries according to the sparsity pattern.
In my case, obtaining the sparsity pattern is not easy without major refactoring of the code behind `f`.
Also, the actual computation of the Jacobian is not too time consuming, I am more worried about the memory requirements for storing entire `J`.
_Thus, my question: Is it possible to use `ForwardDiff.jacobian` (or a related function) such that only the non-zero outcomes are stored (in a sparse format)?_
---
### Author:  [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)
#### Post date: [August 9, 2023, 5:04pm UTC](https://discourse.julialang.org/t/possibility-to-store-outcome-of-forwarddiff-jacobian-already-in-sparse-format/102635/2 "2023-08-09T17:04:40Z")
> [@DanDoe](#):
>
> Thus, my question: Is it possible to use `ForwardDiff.jacobian` (or a related function) such that only the non-zero outcomes are stored (in a sparse format)?
Not really. You could setup a different accumulation using jvps though, basically calculate each vector, call sparse, and concatenate.
---
### Author:  [@brianguenter](https://discourse.julialang.org/u/brianguenter)
#### Post date: [August 11, 2023, 6:19am UTC](https://discourse.julialang.org/t/possibility-to-store-outcome-of-forwarddiff-jacobian-already-in-sparse-format/102635/3 "2023-08-11T06:19:00Z")
[FastDifferentiation.jl](https://github.com/brianguenter/FastDifferentiation.jl) might help you. It’s good at detecting sparsity in Jacobians and stores them directly in a sparse format. It has limitations (see the docs) but if it works for your problem it should be efficient.