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[GamersNexus] Top Amazon Cooler vs. AMD Stock Cooler: $30 Vetroo V5 Air Cooler Review
(Overclock 3D) Smart Access Memory on Radeon's RX 5000 Series Tested - A Free Performance Boost!
AI Benchmark - 11900 Intel Optimized Tensorflow Performance Test
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The Verge: "The Surface Pro X gets a Wi-Fi-only version"

The Verge: "Microsoft announces Surface Pro 8 with bigger 13-inch 120Hz display and Thunderbolt"

Posted: 22 Sep 2021 09:03 AM PDT

submitted by /u/Dakhil
[link] [comments]

[GamersNexus] Top Amazon Cooler vs. AMD Stock Cooler: $30 Vetroo V5 Air Cooler Review

Posted: 22 Sep 2021 09:56 PM PDT

submitted by /u/Hellcloud
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(Overclock 3D) Smart Access Memory on Radeon's RX 5000 Series Tested - A Free Performance Boost!

Posted: 22 Sep 2021 06:59 PM PDT

submitted by /u/RandomCollection
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AI Benchmark - 11900 Intel Optimized Tensorflow Performance Test

Posted: 23 Sep 2021 01:02 AM PDT

I was wondering whether I could get a significant performance uplift by using Intel's optimized TensorFlow build (https://hub.docker.com/r/intel/intel-optimized-tensorflow-avx512). This states it only works with Xeon processors, but you can always try anyway. AI Benchmark (https://ai-benchmark.com/) can run various models for training and interference.

Did it work? Yes, I believe it worked.

Maximum core frequency was lower, and the temperature was higher when using the intel AVX-512 optimized container compared to a vanilla TensorFlow container. This leads me to believe it used heavier instructions.

Results

I recorded about 24% uplift in score on the test. I've also tested my RTX 3090 and I'm adding some results from the AI Benchmark website for comparison. The results look reasonable/in-line.

Model	Inference	Training	AI Score
i9 11900f vanilla	1385	1357	2742
i9 11900f optimized	(+10%) 1518	(+40%) 1893	(+24%) 3411
RTX 3090	22116	22632	44748
AMD Ryzen 9 3950X	1755	1223	2978
Intel Core i9-9940X	1750	1512	3262
Tesla V100 PCIE 32Gb	16530	17865	34394
GeForce GTX 960	2996	3312	6308

I was compelled to run an experiment like this out of curiosity for a while. But decided to jump on this after seeing the horrendous Windows results on the AI-Benchmark on Anandtech (https://www.anandtech.com/show/16535/intel-core-i7-11700k-review-blasting-off-with-rocket-lake/4). The Windows results look so bad (for reasons stated in the article), I'm not sure whether they are reporting the total score or just interference or training.

So, not only does it perform significantly better using the optimized container, but it also performs a lot better on Linux than on Windows.

While setting up this test I came across some information that it might be possible (although not officially supported) to run TensorFlow on the AMD APU's Vega graphics using ROCm, so I might do some digging there and see if I can get it to run on my 5600G.

Test System

PopOS 21.04 (all tests in docker containers / NVidia-docker)
- TF Version: 2.6.0
- AI-Benchmark-v.0.1.2
i9 11900f (power unlocked, up to 210W)
Z590 Asus Maximus Hero
Noctua NH-D15
32GB RAM 4x8 3200/14-14-14-34 B-die
RTX 3090 (Palit)