Re: Re: [PATCH] riscv: Optimize memset

From: zhangfei
Date: Mon May 08 2023 - 22:23:08 EST


From: zhangfei <zhangfei@xxxxxxxxxxxxxx>

> > 5:
> > - sb a1, 0(t0)
> > - addi t0, t0, 1
> > - bltu t0, a3, 5b
> > + sb a1, 0(t0)
> > + sb a1, -1(a3)
> > + li a4, 2
> > + bgeu a4, a2, 6f
> > +
> > + sb a1, 1(t0)
> > + sb a1, 2(t0)
> > + sb a1, -2(a3)
> > + sb a1, -3(a3)
> > + li a4, 6
> > + bgeu a4, a2, 6f
> > +
> > + sb a1, 3(t0)
> > + sb a1, -4(a3)
> > + li a4, 8
> > + bgeu a4, a2, 6f
>
> Why is this check here?

Hi,

I filled head and tail with minimal branching. Each conditional ensures that
all the subsequently used offsets are well-defined and in the dest region.

Although this approach may result in redundant storage, compared to byte by
byte storage, it allows storage instructions to be executed in parallel and
reduces the number of jumps.

I used the code linked below for performance testing and commented on the memset
that calls the arm architecture in the code to ensure it runs properly on the
risc-v platform.

[1] https://github.com/ARM-software/optimized-routines/blob/master/string/bench/memset.c#L53

The testing platform selected RISC-V SiFive U74.The test data is as follows:

Before optimization
---------------------
Random memset (bytes/ns):
memset_call 32K:0.45 64K:0.35 128K:0.30 256K:0.28 512K:0.27 1024K:0.25 avg 0.30

Medium memset (bytes/ns):
memset_call 8B:0.18 16B:0.48 32B:0.91 64B:1.63 128B:2.71 256B:4.40 512B:5.67
Large memset (bytes/ns):
memset_call 1K:6.62 2K:7.02 4K:7.46 8K:7.70 16K:7.82 32K:7.63 64K:1.40

After optimization
---------------------
Random memset bytes/ns):
memset_call 32K:0.46 64K:0.35 128K:0.30 256K:0.28 512K:0.27 1024K:0.25 avg 0.31
Medium memset (bytes/ns )
memset_call 8B:0.27 16B:0.48 32B:0.91 64B:1.64 128B:2.71 256B:4.40 512B:5.67
Large memset (bytes/ns):
memset_call 1K:6.62 2K:7.02 4K:7.47 8K:7.71 16K:7.83 32K:7.63 64K:1.40

>From the results, it can be seen that memset has significantly improved its performance with
a data volume of around 8B, from 0.18 bytes/ns to 0.27 bytes/ns.

Thanks,
Fei Zhang