# `Edifice.SSM.MambaCumsum`
[🔗](https://github.com/blasphemetheus/edifice/blob/main/lib/edifice/ssm/mamba_cumsum.ex#L1)

Mamba variant for experimenting with alternative scan algorithms.

Currently uses Blelloch scan (same as regular Mamba). This module exists
to test alternative approaches like:

- **Hillis-Steele scan**: O(L log L) work but more parallelism per level
- **SSD algorithm**: Mamba-2's chunked matmul approach for tensor cores
- **Chunked scan**: Process in chunks with inter-chunk recurrence

## Current Status

The cumsum-based approach (log-space reformulation) doesn't work well in XLA.
XLA's cumulative_sum kernel is slower than Blelloch's pad/slice/multiply pattern
for this tensor structure.

## Usage

    model = MambaCumsum.build(embed_dim: 287, hidden_size: 256)

# `build_opt`

```elixir
@type build_opt() ::
  {:embed_dim, pos_integer()}
  | {:hidden_size, pos_integer()}
  | {:state_size, pos_integer()}
  | {:expand_factor, pos_integer()}
  | {:conv_size, pos_integer()}
  | {:num_layers, pos_integer()}
  | {:dropout, float()}
  | {:window_size, pos_integer()}
```

Options for `build/1`.

# `build`

```elixir
@spec build([build_opt()]) :: Axon.t()
```

Build a MambaCumsum model for sequence processing.

Same API as `Mamba.build/1`.

# `build_selective_ssm`

```elixir
@spec build_selective_ssm(
  Axon.t(),
  keyword()
) :: Axon.t()
```

Build the SSM with configurable scan algorithm.

This is where we can swap in different scan implementations:
- :blelloch (default) - Work-efficient O(L) work, O(log L) depth
- :cumsum_transposed - Log-space reformulation with transposed cumsum
- :cumsum_logspace - Log-space reformulation on original axis ordering

# `output_size`

```elixir
@spec output_size(keyword()) :: non_neg_integer()
```

# `param_count`

```elixir
@spec param_count(keyword()) :: non_neg_integer()
```

# `recommended_defaults`

```elixir
@spec recommended_defaults() :: keyword()
```

---

*Consult [api-reference.md](api-reference.md) for complete listing*