From 402e421c3da7db1a7696e3f1172de2741c50f250 Mon Sep 17 00:00:00 2001
From: lkcl <lkcl@web>
Date: Mon, 7 Dec 2020 01:19:44 +0000
Subject: [PATCH]

---
 3d_gpu/architecture/dynamic_simd/mul.mdwn | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/3d_gpu/architecture/dynamic_simd/mul.mdwn b/3d_gpu/architecture/dynamic_simd/mul.mdwn
index fa32ee3a8..646c9cd4c 100644
--- a/3d_gpu/architecture/dynamic_simd/mul.mdwn
+++ b/3d_gpu/architecture/dynamic_simd/mul.mdwn
@@ -1,5 +1,7 @@
 # Dynamic Partitioned Multiply
 
+* <https://git.libre-soc.org/?p=ieee754fpu.git;a=blob;f=src/ieee754/part_mul_add/multiply.py;hb=HEAD>
+
 This is complicated!  It is necessary to compute a full NxN matrix of partial multiplication results, then perform a cascade of adds (long multipication, in binary), using PartitionedAdd, which will "automatically" break the results down into segments, at all times, keeping each partitioned result separate.
 
 The [Wallace Tree](https://en.wikipedia.org/wiki/Wallace_tree) algorithm is presently deployed, here: we need to use the (more efficient) [Dadda algorithm](https://en.wikipedia.org/wiki/Dadda_multiplier)
-- 
2.30.2