3 ms·
> but can have a higher throughput if scheduled well Unlikely to be true for matrix multiplications, which have well-defined data dependencies. > and fused mu
by throwawaymaths 4y ago
> but can have a higher throughput if scheduled well
Unlikely to be true for matrix multiplications, which have well-defined data dependencies.
> and fused multiply-add can be as fast as a single multiplication, essentially giving a free addition.
Yes, this supports the assumption that multiplication is the heavy lift.
- tlb 4y agoWith sufficiently parallel hardware, you can do an entire mat4 * mat4 multiplication in 3 cycles. First do all 64 multiplications in parallel, then do 32 adds, then 16 adds to get the final answer. For operations in GF(2) where they claim a result, a multiply is just an AND gate and an add is an XOR gate. So the fully parallel hardware version is 64 AND gates and 48 XOR gates, with a total gate delay of 3. This is a trivial amount of hardware and could easily be an instruction in some alternate universe where it was useful.
- klyrs 4y agoYou missed the part where the "4x4 matrix multiplication" refers to multiplication of NxN matrices logically partitioned into sixteen blocks of size (N/4)x(N/4), done recursively.