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POFast(est) way to write a seqence of integer to global memory?
 

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  1. POFast(est) way to write a seqence of integer to global memory?
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    <p>The task is very simple, writting a seqence of integer variable to memory:</p> <p>Original code:</p> <pre><code>for (size_t i=0; i&lt;1000*1000*1000; ++i) { data[i]=i; }; </code></pre> <p>Parallelized code:</p> <pre><code> size_t stepsize=len/N; #pragma omp parallel num_threads(N) { int threadIdx=omp_get_thread_num(); size_t istart=stepsize*threadIdx; size_t iend=threadIdx==N-1?len:istart+stepsize; #pragma simd for (size_t i=istart; i&lt;iend; ++i) x[i]=i; }; </code></pre> <p>The performance sucks, it takes <strong>1.6 sec</strong> to writing 1G <code>uint64</code> variables (which is equal to 5GB per sec), by simple parallelization (<code>open mp parallel</code>)of the above code, the speed increase abit, but performance still sucks, take <strong>1.4 sec</strong> with 4 threads and 1.35 with 6 threads on a i7 3970.</p> <p>The theortical memory bandwidth of my rig (<strong>i7 3970/64G DDR3-1600</strong>) is <strong>51.2 GB/sec</strong>, for the above example, the achieved memory bandwidth is only about <strong>1/10</strong> of the theoritcal bandwidth, even through the application is pretty much memory-bandwidth-bounded.</p> <p>Anyone know how to improve the code?</p> <p>I wrote alot of memory-bound code on GPU, its pretty easy for GPU to take full advantage of the GPU's device memory bandwidth (e.g. 85%+ of theoritcal bandwidth).</p> <p><strong>EDIT:</strong></p> <p>The code is compiled by Intel ICC 13.1, to 64bit binary, and with maximum optimzation (O3) and AVX code path on, as well as auto-vectorization.</p> <p><strong>UPDATE:</strong></p> <p>I tried all the codes below ( thanks to Paul R), nothing special happens, I believe the compiler is fully capable of doing the kind of simd/vectorization optimization.</p> <p>As for why I want to fill the numbers there, well, long story short: </p> <p>Its part of a high-performance heterogeneous computing algorthim, on the device side, the algorthim is highly efficient to the degree that the multi-GPU set is so fast such that I found the performance bottleneck happen to be when CPU try to write several seqence of numbers to memory.</p> <p>Of cause, knowing that CPU sucks at filling numbers (in contrast, the GPU can fill seqence of number at a speed very close (<strong>238GB/sec</strong> out of <strong>288GB/sec</strong> on GK110 vs a pathetic <strong>5GB/sec</strong> out of <strong>51.2GB/sec</strong> on CPU) to the theorical bandwidth of GPU's global memory), I could change my algorthim a bit, but what make me wonder is why CPU sucks so bad at filling seqence of numbers here. </p> <p>As for memory bandwidth of my rig, I believe the bandwidth (51.2GB) is about correct, based on my <code>memcpy()</code> test, the achieved bandwidth is about <strong>80%+</strong> of the theoritical bandwidth (<strong>>40GB/sec</strong>).</p>
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    1. CODid you try optimizing the code? E.g. use -O3 if you are using `gcc`?
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    2. COAt a minimum, you should try unrolling it. *Armchair optimizing*.
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    3. COTry doing 2 writes per iteration. Maybe 4, 8, 16.
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      1. USMohamad Ali Baydoun
 

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