{"id":7358,"date":"2020-10-27T07:34:41","date_gmt":"2020-10-27T07:34:41","guid":{"rendered":"https:\/\/www.thegioimaychu.vn\/blog\/?p=7358"},"modified":"2020-10-28T00:44:03","modified_gmt":"2020-10-28T00:44:03","slug":"so-sanh-benchmark-hieu-nang-gpu-rtx-3090-vs-rtx-2080-ti-vs-titan-rtx-vs-rtx-6000-8000","status":"publish","type":"post","link":"https:\/\/thegioimaychu.vn\/blog\/ai-hpc\/so-sanh-benchmark-hieu-nang-gpu-rtx-3090-vs-rtx-2080-ti-vs-titan-rtx-vs-rtx-6000-8000-p7358\/","title":{"rendered":"So s\u00e1nh Benchmark hi\u1ec7u n\u0103ng GPU RTX 3090 vs RTX 2080 Ti vs Titan RTX vs RTX 6000\/8000"},"content":{"rendered":"<style>.iblink{color:#975!important;}.iblink:hover{color:orange!important;}<\/style><h1>\u0110i\u1ec3m Benchmark NVIDIA RTX 3090 cho TensorFlow<\/h1>\n<p>\u1ede b\u00e0i n\u00e0y, ch\u00fang t\u00f4i \u0111\u00e3 ti\u1ebfn h\u00e0nh \u0111\u00e1nh gi\u00e1 hi\u1ec7u su\u1ea5t h\u1ecdc s\u00e2u cho TensorFlow tr\u00ean GPU NVIDIA GeForce RTX 3090.<\/p>\n<p>M\u00e1y tr\u1ea1m <a class=\"iblink\" href=\"\/blog\/tag\/deep-learning\/\">Deep Learning<\/a> c\u1ee7a ch\u00fang t\u00f4i \u0111\u01b0\u1ee3c trang b\u1ecb hai GPU RTX 3090 v\u00e0 ch\u00fang t\u00f4i \u0111\u00e3 ch\u1ea1y t\u1eadp l\u1ec7nh \u0111i\u1ec3m chu\u1ea9n \u201ctf_cnn_benchmarks.py\u201d  ti\u00eau chu\u1ea9n \u0111\u01b0\u1ee3c t\u00ecm th\u1ea5y trong github ch\u00ednh th\u1ee9c c\u1ee7a TensorFlow. Ch\u00fang t\u00f4i \u0111\u00e3 th\u1eed nghi\u1ec7m tr\u00ean c\u00e1c m\u1ea1ng sau: ResNet50, ResNet152, Inception v3, Inception v4. H\u01a1n n\u1eefa, ch\u00fang t\u00f4i \u0111\u00e3 ch\u1ea1y c\u00e1c th\u1eed nghi\u1ec7m t\u01b0\u01a1ng t\u1ef1 b\u1eb1ng c\u00e1ch s\u1eed d\u1ee5ng c\u1ea5u h\u00ecnh GPU 1, 2 v\u00e0 4 (\u0111\u1ed1i v\u1edbi ph\u1ea7n 2x RTX 3090 so v\u1edbi 4x 2080Ti). K\u00edch th\u01b0\u1edbc l\u00f4 \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh l\u00e0 k\u00edch th\u01b0\u1edbc l\u1edbn nh\u1ea5t c\u00f3 th\u1ec3 v\u1eeba v\u1edbi b\u1ed9 nh\u1edb GPU c\u00f3 s\u1eb5n.<\/p>\n<h2>C\u00e1c \u0111i\u1ec3m ch\u00ednh v\u00e0 k\u1ebft qu\u1ea3 th\u1ea5y \u0111\u01b0\u1ee3c<\/h2>\n<ul>\n<li>C\u00e1c NVIDIA RTX 3090 v\u01b0\u1ee3t tr\u1ed9i so v\u1edbi t\u1ea5t c\u1ea3 c\u00e1c GPU (h\u00ecnh \u1ea3nh \/ gi\u00e2y) tr\u00ean t\u1ea5t c\u1ea3 c\u00e1c m\u00f4 h\u00ecnh.<\/li>\n<li>H\u1ec7 th\u1ed1ng c\u00f3 2x RTX 3090&gt; 4x RTX 2080 Ti.<\/li>\n<li>\u0110\u1ed1i v\u1edbi h\u1ecdc s\u00e2u, RTX 3090 l\u00e0 GPU c\u00f3 gi\u00e1 tr\u1ecb t\u1ed1t nh\u1ea5t tr\u00ean th\u1ecb tr\u01b0\u1eddng v\u00e0 l\u00e0m gi\u1ea3m \u0111\u00e1ng k\u1ec3 chi ph\u00ed c\u1ee7a m\u1ed9t m\u00e1y tr\u1ea1m AI.<\/li>\n<\/ul>\n<h2>RTX 3090 ResNet 50 TensorFlow Benchmark<img decoding=\"async\" src=\"https:\/\/thegioimaychu.vn\/blog\/wp-content\/uploads\/2020\/10\/tgmc-blog-5f97cceba5843.png\" alt=\"\u0110i\u1ec3m chu\u1ea9n RTX 3090\"><\/h2>\n<table>\n<tbody>\n<tr>\n<td colspan=\"1\" rowspan=\"1\"><\/td>\n<td colspan=\"1\" rowspan=\"1\">1x GPU<\/td>\n<td colspan=\"1\" rowspan=\"1\">2x GPU<\/td>\n<td colspan=\"1\" rowspan=\"1\">k\u00edch th\u01b0\u1edbc l\u00f4<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 2080 Ti<\/td>\n<td colspan=\"1\" rowspan=\"1\">522,52<\/td>\n<td colspan=\"1\" rowspan=\"1\">959,78<\/td>\n<td colspan=\"1\" rowspan=\"1\">128<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 6000<\/td>\n<td colspan=\"1\" rowspan=\"1\">637,56<\/td>\n<td colspan=\"1\" rowspan=\"1\">1248,54<\/td>\n<td colspan=\"1\" rowspan=\"1\">512<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 8000<\/td>\n<td colspan=\"1\" rowspan=\"1\">604,76<\/td>\n<td colspan=\"1\" rowspan=\"1\">1184,52<\/td>\n<td colspan=\"1\" rowspan=\"1\">1024<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">TITAN RTX<\/td>\n<td colspan=\"1\" rowspan=\"1\">646,13<\/td>\n<td colspan=\"1\" rowspan=\"1\">1287.01<\/td>\n<td colspan=\"1\" rowspan=\"1\">512<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 3090<\/td>\n<td colspan=\"1\" rowspan=\"1\">1139.15<\/td>\n<td colspan=\"1\" rowspan=\"1\">2153,53<\/td>\n<td colspan=\"1\" rowspan=\"1\">512<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>RTX 3090 ResNet 152 TensorFlow Benchmark<\/h2>\n<p><img decoding=\"async\" src=\"https:\/\/thegioimaychu.vn\/blog\/wp-content\/uploads\/2020\/10\/tgmc-blog-5f97cced8e075.png\" alt=\"\u0110i\u1ec3m chu\u1ea9n \u0111\u00e0o t\u1ea1o AI 3090\"><\/p>\n<table>\n<tbody>\n<tr>\n<td colspan=\"1\" rowspan=\"1\"><\/td>\n<td colspan=\"1\" rowspan=\"1\">1x GPU<\/td>\n<td colspan=\"1\" rowspan=\"1\">2x GPU<\/td>\n<td colspan=\"1\" rowspan=\"1\">k\u00edch th\u01b0\u1edbc l\u00f4<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 2080 Ti<\/td>\n<td colspan=\"1\" rowspan=\"1\">209,27<\/td>\n<td colspan=\"1\" rowspan=\"1\">348,8<\/td>\n<td colspan=\"1\" rowspan=\"1\">64<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 6000<\/td>\n<td colspan=\"1\" rowspan=\"1\">281,94<\/td>\n<td colspan=\"1\" rowspan=\"1\">519,76<\/td>\n<td colspan=\"1\" rowspan=\"1\">256<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 8000<\/td>\n<td colspan=\"1\" rowspan=\"1\">285,85<\/td>\n<td colspan=\"1\" rowspan=\"1\">529.05<\/td>\n<td colspan=\"1\" rowspan=\"1\">512<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">TITAN RTX<\/td>\n<td colspan=\"1\" rowspan=\"1\">284,87<\/td>\n<td colspan=\"1\" rowspan=\"1\">530,86<\/td>\n<td colspan=\"1\" rowspan=\"1\">256<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 3090<\/td>\n<td colspan=\"1\" rowspan=\"1\">457,45<\/td>\n<td colspan=\"1\" rowspan=\"1\">857,14<\/td>\n<td colspan=\"1\" rowspan=\"1\">256<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>RTX 3090 Inception V3 TensorFlow Benchmark<\/h2>\n<p><img decoding=\"async\" src=\"https:\/\/thegioimaychu.vn\/blog\/wp-content\/uploads\/2020\/10\/tgmc-blog-5f97ccef20263.png\" alt=\"RTX 3090 Benchmarks Deep Learning \"><\/p>\n<table>\n<tbody>\n<tr>\n<td colspan=\"1\" rowspan=\"1\"><\/td>\n<td colspan=\"1\" rowspan=\"1\">1x GPU<\/td>\n<td colspan=\"1\" rowspan=\"1\">2x GPU<\/td>\n<td colspan=\"1\" rowspan=\"1\">Batch size<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 2080 Ti<\/td>\n<td colspan=\"1\" rowspan=\"1\">310.32<\/td>\n<td colspan=\"1\" rowspan=\"1\">569,24<\/td>\n<td colspan=\"1\" rowspan=\"1\">128<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 6000<\/td>\n<td colspan=\"1\" rowspan=\"1\">391.08<\/td>\n<td colspan=\"1\" rowspan=\"1\">737,77<\/td>\n<td colspan=\"1\" rowspan=\"1\">256<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 8000<\/td>\n<td colspan=\"1\" rowspan=\"1\">391,3<\/td>\n<td colspan=\"1\" rowspan=\"1\">754,94<\/td>\n<td colspan=\"1\" rowspan=\"1\">512<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">TITAN RTX<\/td>\n<td colspan=\"1\" rowspan=\"1\">397.09<\/td>\n<td colspan=\"1\" rowspan=\"1\">784,24<\/td>\n<td colspan=\"1\" rowspan=\"1\">256<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 3090<\/td>\n<td colspan=\"1\" rowspan=\"1\">697,98<\/td>\n<td colspan=\"1\" rowspan=\"1\">1296,86<\/td>\n<td colspan=\"1\" rowspan=\"1\">256<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>RTX 3090 Inception V4 TensorFlow Benchmark<\/h2>\n<p><img decoding=\"async\" src=\"https:\/\/thegioimaychu.vn\/blog\/wp-content\/uploads\/2020\/10\/tgmc-blog-5f97ccf0aee17.png\" alt=\"RTX 3090 Benchmarks Deep Learning \"><\/p>\n<table>\n<tbody>\n<tr>\n<td colspan=\"1\" rowspan=\"1\"><\/td>\n<td colspan=\"1\" rowspan=\"1\">1x GPU<\/td>\n<td colspan=\"1\" rowspan=\"1\">2x GPU<\/td>\n<td colspan=\"1\" rowspan=\"1\">Batch size<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 2080 Ti<\/td>\n<td colspan=\"1\" rowspan=\"1\">150,59<\/td>\n<td colspan=\"1\" rowspan=\"1\">247,16<\/td>\n<td colspan=\"1\" rowspan=\"1\">64<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 6000<\/td>\n<td colspan=\"1\" rowspan=\"1\">203,9<\/td>\n<td colspan=\"1\" rowspan=\"1\">392,14<\/td>\n<td colspan=\"1\" rowspan=\"1\">256<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 8000<\/td>\n<td colspan=\"1\" rowspan=\"1\">203,67<\/td>\n<td colspan=\"1\" rowspan=\"1\">384,29<\/td>\n<td colspan=\"1\" rowspan=\"1\">512<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">TITAN RTX<\/td>\n<td colspan=\"1\" rowspan=\"1\">207,98<\/td>\n<td colspan=\"1\" rowspan=\"1\">399,16<\/td>\n<td colspan=\"1\" rowspan=\"1\">256<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 3090<\/td>\n<td colspan=\"1\" rowspan=\"1\">360<\/td>\n<td colspan=\"1\" rowspan=\"1\">679,61<\/td>\n<td colspan=\"1\" rowspan=\"1\">256<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>2x NVIDIA RTX 3090 Vs. 4x RTX 2080 Ti &#8211; C\u1ea5u h\u00ecnh n\u00e0o t\u1ed1t h\u01a1n?<\/h2>\n<p>Nhi\u1ec1u ng\u01b0\u1eddi t\u00f2 m\u00f2 kh\u00f4ng ch\u1ec9 v\u1ec1 s\u1ef1 k\u1ebft h\u1ee3p hi\u1ec7u su\u1ea5t 1:1 c\u1ee7a RTX 3090 v\u00e0 RTX 2080 Ti m\u00e0 c\u00f2n v\u1ec1 hi\u1ec7u su\u1ea5t c\u1ee7a c\u1ea5u h\u00ecnh \u0111a GPU. Nh\u01b0 hi\u1ec7n t\u1ea1i, RTX 3090 c\u00f3 3 khe c\u1eafm PCIe (so v\u1edbi 2 khe c\u1eafm th\u00f4ng th\u01b0\u1eddng nh\u01b0 2080 Ti c\u00f3) tr\u00ean m\u1ed9t bo m\u1ea1ch ch\u1ee7 th\u00f4ng th\u01b0\u1eddng. Do k\u00edch th\u01b0\u1edbc c\u1ee7a n\u00f3, m\u1ed9t m\u00e1y tr\u1ea1m th\u00f4ng th\u01b0\u1eddng hi\u1ec7n ch\u1ec9 c\u00f3 kh\u1ea3 n\u0103ng ch\u1ee9a 2 RTX 3090 (kh\u00f4ng c\u00f3 s\u1eeda \u0111\u1ed5i t\u00f9y ch\u1ec9nh m\u1edf r\u1ed9ng. C\u1ea5u h\u00ecnh 2x RTX 3090 c\u00f3 t\u01b0\u01a1ng \u1ee9ng v\u1edbi c\u1ea5u h\u00ecnh h\u01b0\u1edbng \u0111\u1ebfn hi\u1ec7u n\u0103ng 4x 2080 Ti kh\u00f4ng? N\u00f3i m\u1ed9t c\u00e1ch \u0111\u01a1n gi\u1ea3n l\u00e0 &#8220;c\u00f3&#8221;. H\u00e3y xem k\u1ebft qu\u1ea3 c\u1ee5 th\u1ec3 d\u01b0\u1edbi \u0111\u00e2y.<img decoding=\"async\" src=\"https:\/\/thegioimaychu.vn\/blog\/wp-content\/uploads\/2020\/10\/tgmc-blog-5f97ccf234e03.png\" alt=\"\u0110i\u1ec3m chu\u1ea9n \u0111\u00e0o t\u1ea1o AI\"><\/p>\n<table>\n<tbody>\n<tr>\n<td colspan=\"1\" rowspan=\"1\"><\/td>\n<td colspan=\"1\" rowspan=\"1\">1x GPU<\/td>\n<td colspan=\"1\" rowspan=\"1\">2x GPU<\/td>\n<td colspan=\"1\" rowspan=\"1\">GPU 4x<\/td>\n<td colspan=\"1\" rowspan=\"1\">Batch size<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 2080 Ti<\/td>\n<td colspan=\"1\" rowspan=\"1\">522,52<\/td>\n<td colspan=\"1\" rowspan=\"1\">959,78<\/td>\n<td colspan=\"1\" rowspan=\"1\">1836,61<\/td>\n<td colspan=\"1\" rowspan=\"1\">128<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">RTX 3090<\/td>\n<td colspan=\"1\" rowspan=\"1\">1139.15<\/td>\n<td colspan=\"1\" rowspan=\"1\">2153,53<\/td>\n<td colspan=\"1\" rowspan=\"1\">N \/ A<\/td>\n<td colspan=\"1\" rowspan=\"1\">512<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2 data-renderer-start-pos=\"345\"><span data-renderer-mark=\"true\">Tham s\u1ed1 Benchmark TF CNN<\/span><\/h2>\n<table width=\"143\">\n<tbody>\n<tr>\n<td colspan=\"1\" rowspan=\"1\" width=\"64\">Description<\/td>\n<td colspan=\"1\" rowspan=\"1\" width=\"79\">Type<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">Number of Batches<\/td>\n<td colspan=\"1\" rowspan=\"1\">100<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">Number of Epochs<\/td>\n<td colspan=\"1\" rowspan=\"1\">0.01<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">Data Format<\/td>\n<td colspan=\"1\" rowspan=\"1\">NCHW<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">Optimizer<\/td>\n<td colspan=\"1\" rowspan=\"1\">Momentum<\/td>\n<\/tr>\n<tr>\n<td colspan=\"1\" rowspan=\"1\">Variables<\/td>\n<td colspan=\"1\" rowspan=\"1\">parameter_server<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><span style=\"font-family:Arial,'TimesNewRoman','BitstreamCharter',Times,serif; font-size:16px; font-weight:400;\">NVIDIA RTX 3090 c\u00f3 b\u1ed9 nh\u1edb 24GB GDDR6X v\u00e0 \u0111\u01b0\u1ee3c x\u00e2y d\u1ef1ng v\u1edbi l\u00f5i RT v\u00e0 l\u00f5i Tensor n\u00e2ng cao, b\u1ed9 x\u1eed l\u00fd \u0111a x\u1eed l\u00fd ph\u00e1t tr\u1ef1c tuy\u1ebfn m\u1edbi v\u00e0 b\u1ed9 nh\u1edb G6X si\u00eau nhanh \u0111\u1ec3 t\u0103ng hi\u1ec7u su\u1ea5t \u0111\u00e1ng kinh ng\u1ea1c.<\/span><\/p>\n<h2>Th\u00f4ng tin th\u00eam v\u1ec1 NVIDIA RTX 3090<\/h2>\n<p>So v\u1edbi 4352 l\u00f5i CUDA c\u1ee7a RTX 2080 Ti, RTX 3090 t\u0103ng h\u01a1n g\u1ea5p \u0111\u00f4i v\u1edbi 10496 l\u00f5i CUDA. CUDA Core l\u00e0 GPU t\u01b0\u01a1ng \u0111\u01b0\u01a1ng v\u1edbi l\u00f5i CPU v\u00e0 \u0111\u01b0\u1ee3c t\u1ed1i \u01b0u h\u00f3a \u0111\u1ec3 ch\u1ea1y m\u1ed9t s\u1ed1 l\u01b0\u1ee3ng l\u1edbn c\u00e1c ph\u00e9p t\u00ednh \u0111\u1ed3ng th\u1eddi (x\u1eed l\u00fd song song). Nhi\u1ec1u l\u00f5i CUDA h\u01a1n th\u01b0\u1eddng c\u00f3 ngh\u0129a l\u00e0 hi\u1ec7u su\u1ea5t t\u1ed1t h\u01a1n v\u00e0 x\u1eed l\u00fd \u0111\u1ed3 h\u1ecda chuy\u00ean s\u00e2u nhanh h\u01a1n.<\/p>\n<p><em>Ngu\u1ed3n<\/em> Exxt<\/p>\n<div>____<br \/><b>B\u00e0i vi\u1ebft li\u00ean quan<\/b><\/div>\n<ul>\n<li><a href=\"https:\/\/thegioimaychu.vn\/blog\/?post_type=post&#038;p=23415\">B\u01b0\u1edbc v\u00e0o k\u1ef7 nguy\u00ean tr\u1ee3 l\u00fd AI c\u00e1 nh\u00e2n &#8211; so s\u00e1nh chi ti\u1ebft NVIDIA RTX Spark v\u00e0 DGX Spark<\/a><\/li>\n<li><a href=\"https:\/\/thegioimaychu.vn\/blog\/?post_type=post&#038;p=23322\">NVIDIA RTX PRO 4500 Blackwell Server Edition: B\u01b0\u1edbc nh\u1ea3y v\u1ecdt t\u1eeb th\u1ebf h\u1ec7 L4 cho h\u1ea1 t\u1ea7ng AI suy lu\u1eadn hi\u1ec7u n\u0103ng cao<\/a><\/li>\n<li><a href=\"https:\/\/thegioimaychu.vn\/blog\/?post_type=post&#038;p=23119\">NVIDIA NGC\u2011ready Low\u2011latency Edge AI: Gi\u1ea3i ph\u00e1p cho Retail, Manufacturing v\u00e0 Smart Cities<\/a><\/li>\n<li><a href=\"https:\/\/thegioimaychu.vn\/blog\/?post_type=post&#038;p=23110\">So s\u00e1nh s\u1ee9c m\u1ea1nh c\u1ee7a m\u00e1y t\u00ednh AI DGX Spark v\u1edbi c\u00e1c card GPU m\u00e1y tr\u1ea1m chuy\u00ean nghi\u1ec7p c\u1ee7a NVIDIA<\/a><\/li>\n<li><a href=\"https:\/\/thegioimaychu.vn\/blog\/?post_type=post&#038;p=22969\">T\u1eeb Orin \u0111\u1ebfn Thor: B\u01b0\u1edbc nh\u1ea3y v\u1ecdt ki\u1ebfn tr\u00fac c\u1ee7a NVIDIA JetPack 7.0 v\u00e0 t\u01b0\u01a1ng lai c\u1ee7a robot h\u00ecnh ng\u01b0\u1eddi<\/a><\/li>\n<li><a href=\"https:\/\/thegioimaychu.vn\/blog\/?post_type=post&#038;p=22887\">T\u1ea1i sao g\u1ecdi NVIDIA DGX Spark l\u00e0 Si\u00eau m\u00e1y t\u00ednh AI c\u00e1 nh\u00e2n?<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>&#272;i&#7875;m Benchmark NVIDIA RTX 3090 cho TensorFlow &#7902; b&agrave;i n&agrave;y, ch&uacute;ng t&ocirc;i &#273;&atilde; ti&#7871;n h&agrave;nh &#273;&aacute;nh gi&aacute; hi&#7879;u su&#7845;t h&#7885;c s&acirc;u cho TensorFlow tr&ecirc;n GPU NVIDIA GeForce RTX 3090. M&aacute;y tr&#7841;m Deep Learning c&#7911;a ch&uacute;ng t&ocirc;i &#273;&#432;&#7907;c trang b&#7883; hai GPU RTX 3090 v&agrave; ch&uacute;ng t&ocirc;i &#273;&atilde; ch&#7841;y t&#7853;p l&#7879;nh &#273;i&#7875;m chu&#7849;n &ldquo;tf_cnn_benchmarks.py&rdquo; ti&ecirc;u chu&#7849;n&#8230;<\/p>\n","protected":false},"author":2,"featured_media":7367,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[3,1],"tags":[304,671,1314],"class_list":["post-7358","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-hpc","category-tong-hop","tag-geforce","tag-gpu","tag-nvidia"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>So s\u00e1nh Benchmark hi\u1ec7u n\u0103ng GPU RTX 3090 vs RTX 2080 Ti vs Titan RTX vs RTX 6000\/8000 - Blog | TheGioiMayChu<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/thegioimaychu.vn\/blog\/ai-hpc\/so-sanh-benchmark-hieu-nang-gpu-rtx-3090-vs-rtx-2080-ti-vs-titan-rtx-vs-rtx-6000-8000-p7358\/\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:title\" content=\"So s\u00e1nh Benchmark hi\u1ec7u n\u0103ng GPU RTX 3090 vs RTX 2080 Ti vs Titan RTX vs RTX 6000\/8000 - Blog | TheGioiMayChu\" \/>\n<meta name=\"twitter:description\" content=\"&#272;i&#7875;m Benchmark NVIDIA RTX 3090 cho TensorFlow &#7902; b&agrave;i n&agrave;y, ch&uacute;ng t&ocirc;i &#273;&atilde; ti&#7871;n h&agrave;nh &#273;&aacute;nh gi&aacute; hi&#7879;u su&#7845;t h&#7885;c s&acirc;u cho TensorFlow tr&ecirc;n GPU NVIDIA GeForce RTX 3090. 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