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I want to optimize a computationally intensive loop using SIMD instructions on an Intel Core i7 `12700K` processor and 32GB of DDR4 `3200` memory , to boost the performance for a double precision floating point vector addition operation within a larger scientific computation
section .data
data_array: dq 1.0, 2.0, 3.0, 4.0, ..., 1000000.0 ; Array of 1 million double-precision values
section .text
global my_function
my_function:
mov rcx, 1000000 / 4 ; Loop counter (number of 128-bit chunks)
mov rsi, data_array
loop_start:
movups xmm0, [rsi]
movups xmm1, [rsi + 16]
addps xmm0, xmm1
movups [rsi], xmm0
add rsi, 32
dec rcx
jnz loop_start
ret
I’ve compiled the code with GCC using the -O3 optimization flag. While there is some performance improvement compared to the scalar version, it’s significantly less than expected. I’ve measured a speedup of approximately 1.5x on an Intel Core i7 `12700K` processor.
So I’m looking for suggestions on how to further optimize this code for maximum performance. Are there any specific SIMD instructions or techniques that could be beneficial? Thinking of exploring memory optimization strategies like prefetching or prolly cache blocking
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