Is the SSE unaligned load intrinsic any slower tha

Question

I'm considering changing some code high performance code that currently requires 16 byte aligned arrays and uses _mm_load_ps to relax the alignment constraint and use _mm_loadu_ps. There are a lot of myths about the performance implications of memory alignment for SSE instructions, so I made a small test case of what should be a memory-bandwidth bound loop. Using either the aligned or unaligned load intrinsic, it runs 100 iterations through a large array, summing the elements with SSE intrinsics. The source code is here. https://gist.github.com/rmcgibbo/7689820

The results on a 64 bit Macbook Pro with a Sandy Bridge Core i5 are below. Lower numbers indicate faster performance. As I read the results, I see basically no performance penalty from using _mm_loadu_ps on unaligned memory.

I find this surprising. Is this a fair test / justified conclusion? On what hardware platforms is there a difference?

$ gcc -O3 -msse aligned_vs_unaligned_load.c  && ./a.out  200000000
Array Size: 762.939 MB
Trial 1
_mm_load_ps with aligned memory:    0.175311
_mm_loadu_ps with aligned memory:   0.169709
_mm_loadu_ps with unaligned memory: 0.169904
Trial 2
_mm_load_ps with aligned memory:    0.169025
_mm_loadu_ps with aligned memory:   0.191656
_mm_loadu_ps with unaligned memory: 0.177688
Trial 3
_mm_load_ps with aligned memory:    0.182507
_mm_loadu_ps with aligned memory:   0.175914
_mm_loadu_ps with unaligned memory: 0.173419
Trial 4
_mm_load_ps with aligned memory:    0.181997
_mm_loadu_ps with aligned memory:   0.172688
_mm_loadu_ps with unaligned memory: 0.179133
Trial 5
_mm_load_ps with aligned memory:    0.180817
_mm_loadu_ps with aligned memory:   0.172168
_mm_loadu_ps with unaligned memory: 0.181852

Answer 1

There are two questions here: Are unaligned loads slower than aligned loads given the same aligned addresses? And are loads with unaligned addresses slower than loads with aligned addresses?

Older Intel CPUs (“older” in this case is just a few years ago) did have slight performance penalties for using unaligned load instructions with aligned addresses, compared to aligned loads with new addresses. Newer CPUs tend not to have this issue.

Both older and newer Intel CPUs have performance penalties for loading from unaligned addresses, notably when cache lines are crossed.

Since the details vary from processor model to processor model, you would have to check each one individually for details.

Sometimes performance issues can be masked. Simple sequences of instructions used for measurement might not reveal that unaligned-load instructions are keeping the load-store units busier than aligned-load instructions would, so that there would be a performance degradation if certain additional operations were attempted in the former case but not in the latter.

Answer 2

This is architecture dependent and recent generations have improved things significantly. On the older Core2 architecture on the other hand:

$ gcc -O3 -fno-inline foo2.c -o a; ./a 1000000 
Array Size: 3.815 MB                    
Trial 1
_mm_load_ps with aligned memory:    0.003983
_mm_loadu_ps with aligned memory:   0.003889
_mm_loadu_ps with unaligned memory: 0.008085
Trial 2
_mm_load_ps with aligned memory:    0.002553
_mm_loadu_ps with aligned memory:   0.002567
_mm_loadu_ps with unaligned memory: 0.006444
Trial 3
_mm_load_ps with aligned memory:    0.002557
_mm_loadu_ps with aligned memory:   0.002552
_mm_loadu_ps with unaligned memory: 0.006430
Trial 4
_mm_load_ps with aligned memory:    0.002563
_mm_loadu_ps with aligned memory:   0.002568
_mm_loadu_ps with unaligned memory: 0.006436
Trial 5
_mm_load_ps with aligned memory:    0.002543
_mm_loadu_ps with aligned memory:   0.002565
_mm_loadu_ps with unaligned memory: 0.006400

Answer 3

See "§2.4.5.1 Efficient Handling of Alignment Hazards" in Intel® 64 and IA-32 Architectures Optimization Reference Manual:

The cache and memory subsystems handles a significant percentage of instructions in every workload. Different address alignment scenarios will produce varying performance impact for memory and cache operations. For example, 1-cycle throughput of L1 (see Table 2-25) generally applies to naturally-aligned loads from L1 cache. But using unaligned load instructions (e.g. MOVUPS, MOVUPD, MOVDQU, etc.) to access data from L1 will experience varying amount of delays depending on specific microarchitectures and alignment scenarios.

I couldn't copy the table here, it basically shows that aligned and unaligned L1 loads are 1 cycle; split cache line boundary is ~4.5 cycles.

Answer 4

You have a lot of noise in your results. I re-ran this on a Xeon E3-1230 V2 @ 3.30GHz running Debian 7, doing 12 runs (discarding the first to account for virtual memory noise) over a 200000000 array, with 10 iterations for the i within the benchmark functions, explicit noinline for the functions you provided, and each of your three benchmarks running in isolation: https://gist.github.com/creichen/7690369

This was with gcc 4.7.2.

The noinline ensured that the first benchmark wasn't optimised out.

The exact call being

./a.out 200000000 10 12 $n

for $n from 0 to 2.

Here are the results:

load_ps aligned

min:    0.040655
median: 0.040656
max:    0.040658

loadu_ps aligned

min:    0.040653
median: 0.040655
max:    0.040657

loadu_ps unaligned

min:    0.042349
median: 0.042351
max:    0.042352

As you can see, these are some very tight bounds that show that loadu_ps is slower on unaligned access (slowdown of about 5%) but not on aligned access. Clearly on that particular machine loadu_ps pays no penalty on aligned memory access.

Looking at the assembly, the only difference between the load_ps and loadu_ps versions is that the latter includes a movups instruction, re-orders some other instructions to compensate, and uses slightly different register names. The latter is probably completely irrelevant and the former can get optimised out during microcode translation.

Now, it's hard to tell (without being an Intel engineer with access to more detailed information) whether/how the movups instruction gets optimised out, but considering that the CPU silicon would pay little penalty for simply using the aligned data path if the lower bits in the load address are zero and the unaligned data path otherwise, that seems plausible to me.

I tried the same on my Core i7 laptop and got very similar results.

In conclusion, I would say that yes, you do pay a penalty for unaligned memory access, but it is small enough that it can get swamped by other effects. In the runs you reported there seems to be enough noise to allow for the hypothesis that it is slower for you too (note that you should ignore the first run, since your very first trial will pay a price for warming up the page table and caches.)