{"id":2668,"date":"2020-06-12T04:12:49","date_gmt":"2020-06-12T04:12:49","guid":{"rendered":"https:\/\/www.thegioimaychu.vn\/solution\/?p=2668"},"modified":"2020-06-15T00:35:16","modified_gmt":"2020-06-15T00:35:16","slug":"giai-phap-dien-toan-cho-ai-va-deep-learning-dua-tren-cong-nghe-cua-supermicro","status":"publish","type":"post","link":"https:\/\/thegioimaychu.vn\/solution\/infra\/giai-phap-dien-toan-cho-ai-va-deep-learning-dua-tren-cong-nghe-cua-supermicro-p2668\/","title":{"rendered":"Gi\u1ea3i ph\u00e1p \u0111i\u1ec7n to\u00e1n cho AI v\u00e0 Deep Learning d\u1ef1a tr\u00ean c\u00f4ng ngh\u1ec7 c\u1ee7a Supermicro"},"content":{"rendered":"<h2>N\u1eafm l\u1ea5y AI v\u1edbi c\u00f4ng ngh\u1ec7 Deep Learning c\u1ee7a Supermicro<\/h2>\n<p>Deep Learning, m\u1ed9t t\u1eadp con c\u1ee7a Tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o (AI) v\u00e0 Machine Learning (ML), l\u00e0 quy tr\u00ecnh ti\u00ean ti\u1ebfn trong khoa h\u1ecdc m\u00e1y t\u00ednh th\u1ef1c hi\u1ec7n c\u00e1c m\u1ea1ng th\u1ea7n kinh nh\u00e2n t\u1ea1o \u0111a l\u1edbp \u0111\u1ec3 th\u1ef1c hi\u1ec7n c\u00e1c nhi\u1ec7m v\u1ee5 r\u1ea5t ph\u1ee9c t\u1ea1p \u0111\u1ec3 l\u1eadp tr\u00ecnh.\u00a0V\u00ed d\u1ee5: Google Maps x\u1eed l\u00fd h\u00e0ng tri\u1ec7u \u0111i\u1ec3m d\u1eef li\u1ec7u m\u1ed7i ng\u00e0y \u0111\u1ec3 t\u00ecm ra tuy\u1ebfn \u0111\u01b0\u1eddng t\u1ed1t nh\u1ea5t cho vi\u1ec7c di chuy\u1ec3n ho\u1eb7c d\u1ef1 \u0111o\u00e1n th\u1eddi gian \u0111\u1ec3 \u0111\u1ebfn \u0111\u00edch mong mu\u1ed1n.\u00a0Deep Learning bao g\u1ed3m hai ph\u1ea7n &#8211; \u0111\u00e0o t\u1ea1o (training) v\u00e0 suy lu\u1eadn (inference).\u00a0Ph\u1ea7n \u0111\u00e0o t\u1ea1o c\u1ee7a Deep Learning bao g\u1ed3m x\u1eed l\u00fd c\u00e0ng nhi\u1ec1u \u0111i\u1ec3m d\u1eef li\u1ec7u c\u00e0ng t\u1ed1t \u0111\u1ec3 l\u00e0m cho m\u1ea1ng th\u1ea7n kinh t\u1ef1 &#8216;h\u1ecdc&#8217; \u0111\u1eb7c t\u00ednh v\u00e0 t\u1ef1 s\u1eeda \u0111\u1ed5i \u0111\u1ec3 ho\u00e0n th\u00e0nh c\u00e1c nhi\u1ec7m v\u1ee5 nh\u01b0 nh\u1eadn d\u1ea1ng h\u00ecnh \u1ea3nh, nh\u1eadn d\u1ea1ng gi\u1ecdng n\u00f3i, v.v&#8230; Ph\u1ea7n suy lu\u1eadn \u0111\u1ec1 c\u1eadp \u0111\u1ebfn qu\u00e1 tr\u00ecnh l\u1ea5y m\u1ed9t m\u00f4 h\u00ecnh \u0111\u00e3 \u0111\u01b0\u1ee3c \u0111\u00e0o t\u1ea1o tr\u01b0\u1edbc \u0111\u00f3 v\u00e0 s\u1eed d\u1ee5ng n\u00f3 \u0111\u1ec3 \u0111\u01b0a ra nh\u1eefng d\u1ef1 \u0111o\u00e1n v\u00e0 quy\u1ebft \u0111\u1ecbnh h\u1eefu \u00edch.<\/p>\n<h2>N\u1ec1n t\u1ea3ng AI &amp; Deep Learning<\/h2>\n<p>Gi\u1ea3i ph\u00e1p c\u1ee7a Supermicro l\u00e0 c\u00e0i \u0111\u1eb7t c\u00e1c framework t\u00f9y bi\u1ebfn cho Deep Learning, \u0111\u1ec3 ng\u01b0\u1eddi d\u00f9ng cu\u1ed1i c\u00f3 th\u1ec3 tr\u1ef1c ti\u1ebfp b\u1eaft \u0111\u1ea7u tri\u1ec3n khai c\u00e1c d\u1ef1 \u00e1n Deep Learning m\u00e0 th\u1eadm ch\u00ed kh\u00f4ng c\u1ea7n \u0111\u1ee5ng \u0111\u1ebfn l\u1eadp tr\u00ecnh GPU. C\u00e1c gi\u1ea3i ph\u00e1p cung c\u1ea5p c\u00e0i \u0111\u1eb7t t\u00f9y bi\u1ebfn c\u00e1c framework h\u1ecdc s\u00e2u bao g\u1ed3m TensorFlow, Ca\ufb00e2, MxNet, Chainer, Microsoft Cognitive Toolkit c\u0169ng nh\u01b0 c\u00e1c b\u1ed9 c\u00f4ng c\u1ee5 kh\u00e1c.<\/p>\n<p>Gi\u1ea3i ph\u00e1p Supermicro AI &amp; Deep Learning cung c\u1ea5p m\u1ed9t l\u1edbp ph\u1ea7n m\u1ec1m AI \/ Deep Learning ho\u00e0n ch\u1ec9nh. B\u00ean d\u01b0\u1edbi l\u00e0 c\u00e1c b\u1ed9 ph\u1ea7n m\u1ec1m k\u00e8m v\u1edbi gi\u1ea3i ph\u00e1p t\u00edch h\u1ee3p \u0111\u1ea7y \u0111\u1ee7 t\u1eeb \u0111\u1ea7u \u0111\u1ebfn cu\u1ed1i:<\/p>\n<table class=\"table\">\n<thead>\n<tr>\n<th colspan=\"3\">Ph\u1ea7n m\u1ec1m cho AI &amp; Deep Learning<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th rowspan=\"4\" scope=\"rowgroup\">M\u00f4i tr\u01b0\u1eddng Deep Learning<\/th>\n<th scope=\"row\">Framework<\/th>\n<td>Caffe, Caffe2, Caffe-MPI, Chainer, Microsoft CNTK, Keras, MXNet, TensorFlow, Theano, PyTorch<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Libraries<\/th>\n<td>cnDNN, NCCL, cuBLAS<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">User Access<\/th>\n<td>NVIDIA DIGITS<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Operating Systems<\/th>\n<td>Ubuntu, Docker, Docker NVIDIA<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\u01afu \u0111i\u1ec3m c\u1ee7a gi\u1ea3i ph\u00e1p\u00a0AI &amp; Deep Learning do<\/h2>\n<h2>Supermicro cung c\u1ea5p<\/h2>\n<ul>\n<li><strong>M\u1ed9t &#8220;powerhouse&#8221; cho \u0111i\u1ec7n to\u00e1n to\u00e1n<\/strong>\n<ul>\n<li>C\u1ee5m m\u00e1y t\u00ednh Supermicro AI &amp; Deep Learning \u0111\u01b0\u1ee3c cung c\u1ea5p b\u1edfi c\u00e1c h\u1ec7 th\u1ed1ng Supermicro SuperServer\u00ae, l\u00e0 nh\u1eefng powerhouse c\u00f3 m\u1eadt \u0111\u1ed9 cao v\u00e0 nh\u1ecf g\u1ecdn cho vi\u1ec7c x\u1eed l\u00fd.\u00a0C\u1ee5m \u0111\u01b0\u1ee3c trang b\u1ecb GPU m\u1edbi nh\u1ea5t t\u1eeb \u200b\u200b\u0111\u1ed1i t\u00e1c NVIDIA.\u00a0M\u1ed7i node x\u1eed l\u00fd s\u1eed d\u1ee5ng GPU NVIDIA\u00ae Tesla\u00ae V100.<\/li>\n<\/ul>\n<\/li>\n<li><strong>X\u1eed l\u00fd song song m\u1eadt \u0111\u1ed9 cao<\/strong>\n<ul>\n<li>L\u00ean \u0111\u1ebfn 32 GPU v\u1edbi b\u1ed9 nh\u1edb GPU l\u00ean \u0111\u1ebfn 1TB cho kh\u1ea3 n\u0103ng x\u1eed l\u00fd song song t\u1ed1i \u0111a, gi\u00fap gi\u1ea3m th\u1eddi gian \u0111\u00e0o t\u1ea1o cho workload ch\u1ea1y h\u1ec7 th\u1ed1ng Deep Learning.<\/li>\n<\/ul>\n<\/li>\n<li><strong>T\u0103ng b\u0103ng th\u00f4ng v\u1edbi NVLink<\/strong>\n<ul>\n<li>S\u1eed d\u1ee5ng c\u00f4ng ngh\u1ec7 NVLink\u2122, cho ph\u00e9p giao ti\u1ebfp GPU-GPU nhanh h\u01a1n, n\u00e2ng cao h\u01a1n n\u1eefa hi\u1ec7u n\u0103ng h\u1ec7 th\u1ed1ng trong c\u00e1c Deep Learning workload l\u1edbn.<\/li>\n<\/ul>\n<\/li>\n<li><strong>X\u1eed l\u00fd nhanh h\u01a1n v\u1edbi Tensor Core<\/strong>\n<ul>\n<li>GPU NVIDIA Tesla V100 s\u1eed d\u1ee5ng ki\u1ebfn \u200b\u200btr\u00fac Tensor Core.\u00a0C\u00e1c Tensor Cores ch\u1ee9a h\u1ed7 tr\u1ee3 Deep Learning v\u00e0 c\u00f3 th\u1ec3 cung c\u1ea5p t\u1edbi 125 TFLOPS cho c\u00e1c \u1ee9ng d\u1ee5ng \u0111\u00e0o t\u1ea1o v\u00e0 suy lu\u1eadn.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Thi\u1ebft k\u1ebf m\u1edf r\u1ed9ng<\/strong>\n<ul>\n<li>Ki\u1ebfn tr\u00fac m\u1edf r\u1ed9ng v\u1edbi n\u1ec1n t\u1ea3ng fibre 100G IB EDR, ho\u00e0n to\u00e0n c\u00f3 th\u1ec3 m\u1edf r\u1ed9ng \u0111\u1ec3 ph\u00f9 h\u1ee3p v\u1edbi s\u1ef1 ph\u00e1t tri\u1ec3n trong t\u01b0\u01a1ng lai.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Rapid Flash Xtreme (RFX) &#8211; L\u01b0u tr\u1eef NVMe all-flash hi\u1ec7u su\u1ea5t cao<\/strong>\n<ul>\n<li>RFX l\u00e0 h\u1ec7 th\u1ed1ng l\u01b0u tr\u1eef ho\u00e0n ch\u1ec9nh h\u00e0ng \u0111\u1ea7u, \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n v\u00e0 th\u1eed nghi\u1ec7m ho\u00e0n to\u00e0n cho c\u00e1c \u1ee9ng d\u1ee5ng AI &amp; Deep Learning k\u1ebft h\u1ee3p v\u1edbi Supermicro BigTwin\u2122 c\u00f9ng v\u1edbi h\u1ec7 th\u1ed1ng l\u01b0u tr\u1eef song song WekaIO.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3 class=\"featured\">Ki\u1ebfn \u200b\u200btr\u00fac tham kh\u1ea3o cho h\u1ec7 th\u1ed1ng AI &amp; Deep Learning<\/h3>\n<p>Supermicro hi\u1ec7n \u0111ang cung c\u1ea5p c\u00e1c gi\u1ea3i ph\u00e1p ho\u00e0n ch\u1ec9nh sau \u0111\u00e2y \u0111\u00e3 \u0111\u01b0\u1ee3c ki\u1ec3m tra k\u1ef9 l\u01b0\u1ee1ng v\u00e0 s\u1eb5n s\u00e0ng ho\u1ea1t \u0111\u1ed9ng.\u00a0C\u00e1c c\u1ee5m n\u00e0y c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c thu nh\u1ecf l\u00ean xu\u1ed1ng \u0111\u1ec3 \u0111\u00e1p \u1ee9ng nhu c\u1ea7u c\u1ee7a c\u00e1c d\u1ef1 \u00e1n Deep Learning c\u1ee7a b\u1ea1n.<\/p>\n<table class=\"table\">\n<thead>\n<tr>\n<td><\/td>\n<td><img decoding=\"async\" src=\"https:\/\/thegioimaychu.vn\/solution\/wp-content\/uploads\/-000\/\/1\/sku-14U.png\" alt=\"14U Rack Solution\" \/><\/td>\n<td><img decoding=\"async\" src=\"https:\/\/thegioimaychu.vn\/solution\/wp-content\/uploads\/-000\/\/1\/sku-24U.png\" alt=\"24U Rack Solution\" \/><\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td>\n<h3>14U Rack<\/h3>\n<\/td>\n<td>\n<h3>24U Rack<\/h3>\n<\/td>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th scope=\"row\">Product SKU<\/th>\n<td><strong>SRS-14UGPU-AIV1-01<\/strong><\/td>\n<td><strong>SRS-24UGPU-AIV1-01<\/strong><\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Compute Capability<\/th>\n<td>2PFLOPS (GPU FP16)<\/td>\n<td>4PFLOPS (GPU FP16)<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Compute Node<\/th>\n<td>2 SYS-4029GP-TVRT<\/td>\n<td>4 SYS-4029GP-TVRT<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Total GPUs<\/th>\n<td>16 NVIDIA\u00ae Tesla\u00ae V100 SXM2 32GB HBM<\/td>\n<td>32 NVIDIA\u00ae Tesla\u00ae V100 SXM2 32GB HBM<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Total GPU Memory<\/th>\n<td>512GB HBM2<\/td>\n<td>1TB HBM2<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Total CPU<\/th>\n<td>4 Intel\u00ae Xeon\u00ae Gold 6154, 3.00GHz, 18-cores<\/td>\n<td>8 Intel\u00ae Xeon\u00ae Gold 6154, 3.00GHz, 18-cores<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Total System Memory<\/th>\n<td>768GB DDR4-2666MHz ECC<\/td>\n<td>3TB DDR4-2666MHz ECC<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Networking<\/th>\n<td>InfiniBand EDR 100Gbps; 10GBASE-T Ethernet<\/td>\n<td>InfiniBand EDR 100Gbps; 10GBASE-T Ethernet<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Total Storage*<\/th>\n<td>15.2TB (8 SATA3 SSDs)<\/td>\n<td>30.4TB (16 SATA3 SSDs)<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Operating System<\/th>\n<td>Ubuntu Linux OS or CentOS Linux<\/td>\n<td>Ubuntu Linux OS or CentOS Linux<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Software<\/th>\n<td>Caffe, Caffe2, Digits, Inference Server, PyTorch, NVIDIA\u00ae CUDA\u00ae, NVIDIA\u00ae TensorRT\u2122, Microsoft Cognitive Toolkit (CNKT), MXNet, TensorFlow, Theano, and Torch<\/td>\n<td>Caffe, Caffe2, Digits, Inference Server, PyTorch, NVIDIA\u00ae CUDA\u00ae, NVIDIA\u00ae TensorRT\u2122, Microsoft Cognitive Toolkit (CNKT), MXNet, TensorFlow, Theano, and Torch<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Max Power Usage<\/th>\n<td>7.2kW (7,200W)<\/td>\n<td>14.0kW (14,000kW)<\/td>\n<\/tr>\n<tr>\n<th scope=\"row\">Dimensions<\/th>\n<td>14 Rack Units, 600 x 800 x 1000 (mm, W x H x D)<\/td>\n<td>24 Rack Units, 598 x 1163 x 1000 (mm, W x H x D)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2><\/h2>\n<h3 class=\"featured\">C\u00e1c n\u1ec1n t\u1ea3ng m\u00e1y ch\u1ee7 s\u1eb5n s\u00e0ng cho AI &amp; Deep Learning t\u1eeb Supermicro<\/h3>\n<h3><a href=\"https:\/\/thegioimaychu.vn\/search\/?search=SYS-1029GQ-TVRT&qt=sku&ref=tmsol\" class=\"sku-link\">SYS-1029GQ-TVRT<\/a><\/h3>\n<p>&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<th><img loading=\"lazy\" decoding=\"async\" class=\"\" src=\"https:\/\/thegioimaychu.vn\/solution\/wp-content\/uploads\/-000\/\/1\/SYS-1029GQ-TVRT_angle.png\" alt=\"SYS-1029GQ-TVRT\" width=\"152\" height=\"105\" \/><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"\" src=\"https:\/\/thegioimaychu.vn\/solution\/wp-content\/uploads\/-000\/\/1\/SYS-1029GQ-TVRT_rear.png\" alt=\"SYS-1029GQ-TVRT (rear)\" width=\"153\" height=\"32\" \/><\/th>\n<td>\n<ul>\n<li>HPC, Artificial Intelligence, Big Data Analytics, Research Lab, Astrophysics, Business Intelligence<\/li>\n<li>Dual Socket P (LGA 3647) support: 2nd Gen. Intel\u00ae Xeon\u00ae Scalable processors; dual UPI up to 10.4GT\/s<\/li>\n<li>12 DIMMs; up to 3TB 3DS ECC DDR4-2933 MHz RDIMM\/LRDIMM<\/li>\n<li>Supports Intel\u00ae Optane\u2122 DCPMM*<\/li>\n<li>2 Hot-swap 2.5&#8243; drive bays, 2 Internal 2.5&#8243; drive bays<\/li>\n<li>4 PCI-E 3.0 x16 slots<\/li>\n<li>2x 10GBase-T ports via Intel X540, 1 Dedicated IPMI port<\/li>\n<li>1 VGA, 2 COM, 2 USB 3.0 (rear)<\/li>\n<li>7x 4cm heavy duty counter-rotating fans with air shroud<\/li>\n<li>2000W Redundant\u00a0<strong>Titanium<\/strong>\u00a0Level (96%) Power Supplies<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<h3><a href=\"https:\/\/thegioimaychu.vn\/search\/?search=SYS-4029GP-TVRT&qt=sku&ref=tmsol\" class=\"sku-link\">SYS-4029GP-TVRT<\/a><\/h3>\n<table>\n<tbody>\n<tr>\n<th><img loading=\"lazy\" decoding=\"async\" class=\"\" src=\"https:\/\/thegioimaychu.vn\/solution\/wp-content\/uploads\/-000\/\/1\/SYS-4029GP-TVRT_angle.png\" alt=\"SYS-4029GP-TVRT\" width=\"152\" height=\"103\" \/><br \/>\n<img loading=\"lazy\" decoding=\"async\" class=\"\" src=\"https:\/\/thegioimaychu.vn\/solution\/wp-content\/uploads\/-000\/\/1\/SYS-4029GP-TVRT_rear.png\" alt=\"SYS-4029GP-TVRT (rear)\" width=\"152\" height=\"74\" \/><\/th>\n<td>\n<ul>\n<li>Artificial Intelligence, Big Data Analytics, High-performance Computing, Research Lab\/National Lab, Astrophysics, Business Intelligence<\/li>\n<li>Dual Socket P (LGA 3647) support: 2nd Gen. Intel\u00ae Xeon\u00ae Scalable processors; 3 UPI up to 10.4GT\/s<\/li>\n<li>24 DIMMs; up to 6TB 3DS ECC DDR4-2933 MHz RDIMM\/LRDIMM<\/li>\n<li>Supports Intel\u00ae Optane\u2122 DCPMM*<\/li>\n<li>16 Hot-swap 2.5&#8243; drive bays (support 8 NVMe drives)<\/li>\n<li>4 PCI-E 3.0 x16 (LP, GPU tray for GPUDirect RDMA), 2 PCI-E 3.0 x16 (LP, CPU tray)<\/li>\n<li>2x 10GBase-T ports via Intel X540, 1 Dedicated IPMI port<\/li>\n<li>1 VGA, 1 COM, 2 USB 3.0 (front)<\/li>\n<li>8x 92mm cooling fans, 4x 80mm cooling fans<\/li>\n<li>2200W (2+2) Redundant\u00a0<strong>Titanium<\/strong>\u00a0Level (96%) Power Supplies<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<h3><a href=\"https:\/\/thegioimaychu.vn\/search\/?search=SYS-6049GP-TRT&qt=sku&ref=tmsol\" class=\"sku-link\">SYS-6049GP-TRT<\/a><\/h3>\n<table>\n<tbody>\n<tr>\n<th><img loading=\"lazy\" decoding=\"async\" class=\"\" src=\"https:\/\/thegioimaychu.vn\/solution\/wp-content\/uploads\/-000\/\/1\/SYS-6049GP-TRT_angle.png\" alt=\"SYS-6049GP-TRT\" width=\"152\" height=\"121\" \/><br \/>\n<img loading=\"lazy\" decoding=\"async\" class=\"\" src=\"https:\/\/thegioimaychu.vn\/solution\/wp-content\/uploads\/-000\/\/1\/SYS-6049GP-TRT_rear.png\" alt=\"SYS-6049GP-TRT (rear)\" width=\"152\" height=\"75\" \/><\/th>\n<td>\n<ul>\n<li>AI\/Deep Learning, Video Transcoding<\/li>\n<li>Dual Socket P (LGA 3647) support: 2nd Gen. Intel\u00ae Xeon\u00ae Scalable processors; 3 UPI up to 10.4GT\/s<\/li>\n<li>24 DIMMs; up to 6TB 3DS ECC DDR4-2933 MHz RDIMM\/LRDIMM<\/li>\n<li>Supports Intel\u00ae Optane\u2122 DCPMM*<\/li>\n<li>24 Hot-swap 3.5&#8243; drive bays, 2 optional 2.5&#8243; U.2 NVMe drives<\/li>\n<li>20 PCI-E 3.0 x16 slots, 1 PCI-E 3.0 x8 (FHFL, in x16 slot)<\/li>\n<li>2x 10GBase-T ports via Intel C622, 1 Dedicated IPMI port<\/li>\n<li>1 VGA, 1 COM, 4 USB 3.0 (rear)<\/li>\n<li>8x 92mm RPM Hot-Swappable Cooling Fans<\/li>\n<li>2000W (2+2) Redundant\u00a0<strong>Titanium<\/strong>\u00a0Level (96%) Power Supplies<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<h3><a href=\"https:\/\/thegioimaychu.vn\/search\/?search=SYS-9029GP-TNVRT&qt=sku&ref=tmsol\" class=\"sku-link\">SYS-9029GP-TNVRT<\/a><\/h3>\n<table>\n<tbody>\n<tr>\n<th><img loading=\"lazy\" decoding=\"async\" class=\"\" src=\"https:\/\/thegioimaychu.vn\/solution\/wp-content\/uploads\/-000\/\/1\/SYS-9029GP-TNVRT_angle.png\" alt=\"SYS-9029GP-TNVRT\" width=\"152\" height=\"108\" \/><br \/>\n<img loading=\"lazy\" decoding=\"async\" class=\"\" src=\"https:\/\/thegioimaychu.vn\/solution\/wp-content\/uploads\/-000\/\/1\/SYS-9029GP-TNVRT_rear.png\" alt=\"SYS-9029GP-TNVRT (rear)\" width=\"152\" height=\"161\" \/><\/th>\n<td>\n<ul>\n<li>AI\/Deep Learning, High-performance Computing<\/li>\n<li>Dual Socket P (LGA 3647) support: 2nd Gen. 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