From 8cd67b6ef293b164922066cd6285c45e18cd7d45 Mon Sep 17 00:00:00 2001 From: lkcl Date: Sun, 17 Jan 2021 01:31:28 +0000 Subject: [PATCH] --- 3d_gpu/architecture/dynamic_simd/mul.mdwn | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/3d_gpu/architecture/dynamic_simd/mul.mdwn b/3d_gpu/architecture/dynamic_simd/mul.mdwn index 646c9cd4c..b350aac64 100644 --- a/3d_gpu/architecture/dynamic_simd/mul.mdwn +++ b/3d_gpu/architecture/dynamic_simd/mul.mdwn @@ -4,4 +4,8 @@ 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. +Therefore, for a full 64 bit multiply, with 7 partitions, a matrix of 8x8 multiplications are performed, then added up in each column of the same magnitude, in exactly the same way as described by Vedic Mathematics, + + + 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