{"id":24467,"date":"2026-04-27T10:32:35","date_gmt":"2026-04-27T03:32:35","guid":{"rendered":"https:\/\/vnso.vn\/?p=24467"},"modified":"2026-04-27T10:32:35","modified_gmt":"2026-04-27T03:32:35","slug":"nvidia-a100-sxm4-80gb-gpu-thong-so-cau-hinh-chinh-hang","status":"publish","type":"post","link":"https:\/\/vnso.vn\/en\/nvidia-a100-sxm4-80gb-gpu-thong-so-cau-hinh-chinh-hang\/","title":{"rendered":"NVIDIA A100 SXM4 80GB GPU th\u00f4ng s\u1ed1 c\u1ea5u h\u00ecnh ch\u00ednh h\u00e3ng"},"content":{"rendered":"

NVIDIA A100 SXM4 80GB l\u00e0 GPU data center \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf cho c\u00e1c h\u1ec7 th\u1ed1ng AI v\u00e0 HPC quy m\u00f4 l\u1edbn, n\u01a1i y\u00eau c\u1ea7u kh\u00f4ng ch\u1ec9 n\u1eb1m \u1edf s\u1ee9c m\u1ea1nh t\u00ednh to\u00e1n m\u00e0 c\u00f2n \u1edf kh\u1ea3 n\u0103ng x\u1eed l\u00fd d\u1eef li\u1ec7u li\u00ean t\u1ee5c v\u1edbi \u0111\u1ed9 tr\u1ec5 th\u1ea5p. \u0110\u00e2y l\u00e0 phi\u00ean b\u1ea3n hi\u1ec7u n\u0103ng cao nh\u1ea5t c\u1ee7a d\u00f2ng A100, s\u1eed d\u1ee5ng form factor SXM4 thay v\u00ec PCIe, th\u01b0\u1eddng \u0111\u01b0\u1ee3c tri\u1ec3n khai trong c\u00e1c h\u1ec7 th\u1ed1ng nh\u01b0 HGX ho\u1eb7c DGX.<\/p>\n

Kh\u00e1c v\u1edbi GPU th\u00f4ng th\u01b0\u1eddng, A100 SXM4 ho\u1ea1t \u0111\u1ed9ng nh\u01b0 m\u1ed9t compute module g\u1eafn tr\u1ef1c ti\u1ebfp l\u00ean mainboard server, cho ph\u00e9p t\u1eadn d\u1ee5ng t\u1ed1i \u0111a \u0111i\u1ec7n n\u0103ng, b\u0103ng th\u00f4ng v\u00e0 kh\u1ea3 n\u0103ng k\u1ebft n\u1ed1i gi\u1eefa nhi\u1ec1u GPU.<\/p>\n

NVIDIA A100 SXM4 80GB l\u00e0 g\u00ec?<\/h2>\n

\u0110\u1ec3 hi\u1ec3u NVIDIA A100 SXM4 80GB, c\u1ea7n t\u00e1ch r\u00f5 t\u1eebng th\u00e0nh ph\u1ea7n trong t\u00ean g\u1ecdi.<\/p>\n

\u201cNVIDIA<\/strong>\u201d l\u00e0 nh\u00e0 s\u1ea3n xu\u1ea5t GPU h\u00e0ng \u0111\u1ea7u th\u1ebf gi\u1edbi, t\u1eadp trung m\u1ea1nh v\u00e0o AI v\u00e0 data center. \u201cA100\u201d l\u00e0 t\u00ean d\u00f2ng GPU thu\u1ed9c ki\u1ebfn tr\u00fac Ampere, \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf chuy\u00ean bi\u1ec7t cho x\u1eed l\u00fd tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o v\u00e0 t\u00ednh to\u00e1n hi\u1ec7u n\u0103ng cao. \u201c80GB\u201d th\u1ec3 hi\u1ec7n dung l\u01b0\u1ee3ng b\u1ed9 nh\u1edb VRAM c\u1ef1c l\u1edbn, cho ph\u00e9p x\u1eed l\u00fd c\u00e1c m\u00f4 h\u00ecnh d\u1eef li\u1ec7u kh\u1ed5ng l\u1ed3. \u201cSXM4\u201d l\u00e0 d\u1ea1ng thi\u1ebft k\u1ebf ph\u1ea7n c\u1ee9ng d\u00e0nh ri\u00eang cho server, kh\u00e1c ho\u00e0n to\u00e0n v\u1edbi card PCIe th\u01b0\u1eddng th\u1ea5y tr\u00ean m\u00e1y t\u00ednh.<\/p>\n

A100 SXM4 80GB l\u00e0 m\u1ed9t \u201cb\u1ed9 n\u00e3o t\u00ednh to\u00e1n\u201d d\u00e0nh cho trung t\u00e2m d\u1eef li\u1ec7u, n\u01a1i c\u00e1c doanh nghi\u1ec7p ho\u1eb7c t\u1ed5 ch\u1ee9c s\u1eed d\u1ee5ng \u0111\u1ec3 hu\u1ea5n luy\u1ec7n AI, ch\u1ea1y m\u00f4 h\u00ecnh machine learning ho\u1eb7c x\u1eed l\u00fd d\u1eef li\u1ec7u \u1edf quy m\u00f4 r\u1ea5t l\u1edbn.<\/p>\n

M\u1ed9t c\u00e1ch d\u1ec5 h\u00ecnh dung, n\u1ebfu GPU gaming gi\u1ed1ng nh\u01b0 \u0111\u1ed9ng c\u01a1 c\u1ee7a m\u1ed9t chi\u1ebfc xe c\u00e1 nh\u00e2n, th\u00ec A100 SXM4 gi\u1ed1ng nh\u01b0 \u0111\u1ed9ng c\u01a1 c\u1ee7a m\u1ed9t nh\u00e0 m\u00e1y c\u00f4ng nghi\u1ec7p. N\u00f3 kh\u00f4ng ph\u1ee5c v\u1ee5 m\u1ed9t t\u00e1c v\u1ee5 \u0111\u01a1n l\u1ebb m\u00e0 x\u1eed l\u00fd h\u00e0ng tri\u1ec7u ph\u00e9p t\u00ednh m\u1ed7i gi\u00e2y cho c\u00e1c h\u1ec7 th\u1ed1ng ph\u1ee9c t\u1ea1p.<\/p>\n

Trong th\u1ef1c t\u1ebf, A100 SXM4 \u0111\u01b0\u1ee3c tri\u1ec3n khai theo c\u1ee5m nhi\u1ec1u GPU trong c\u00e1c h\u1ec7 th\u1ed1ng nh\u01b0 HGX<\/strong> ho\u1eb7c DGX<\/strong>. Khi \u0111\u00f3, nhi\u1ec1u GPU s\u1ebd k\u1ebft n\u1ed1i v\u1edbi nhau \u0111\u1ec3 x\u1eed l\u00fd m\u1ed9t m\u00f4 h\u00ecnh AI l\u1edbn.<\/p>\n

Ngo\u00e0i ra, dung l\u01b0\u1ee3ng 80GB HBM2e l\u00e0 y\u1ebfu t\u1ed1 quan tr\u1ecdng gi\u00fap GPU n\u00e0y ch\u1ea1y \u0111\u01b0\u1ee3c c\u00e1c m\u00f4 h\u00ecnh AI l\u1edbn. C\u00f3 th\u1ec3 hi\u1ec3u \u0111\u01a1n gi\u1ea3n r\u1eb1ng VRAM c\u00e0ng l\u1edbn th\u00ec GPU c\u00e0ng x\u1eed l\u00fd \u0111\u01b0\u1ee3c m\u00f4 h\u00ecnh ph\u1ee9c t\u1ea1p h\u01a1n.<\/p>\n

>>> Xem chi ti\u1ebft t\u1ea1i NVIDIA A100 l\u00e0 g\u00ec? Ph\u00e2n t\u00edch chi ti\u1ebft t\u1eeb A-Z<\/a><\/strong><\/p>\n

\"GPU<\/a><\/h3>\n

T\u1ed5ng quan v\u1ec1 NVIDIA A100 SXM4 80GB<\/h3>\n

A100 SXM4 \u0111\u01b0\u1ee3c x\u00e2y d\u1ef1ng tr\u00ean ki\u1ebfn tr\u00fac Ampere v\u1edbi GPU GA100, m\u1ed9t trong nh\u1eefng chip ph\u1ee9c t\u1ea1p nh\u1ea5t c\u1ee7a NVIDIA d\u00e0nh cho data center.<\/p>\n

GPU n\u00e0y \u0111\u01b0\u1ee3c s\u1ea3n xu\u1ea5t tr\u00ean ti\u1ebfn tr\u00ecnh 7nm c\u1ee7a TSMC, ch\u1ee9a kho\u1ea3ng 54,2 t\u1ef7 transistor v\u00e0 c\u00f3 di\u1ec7n t\u00edch die l\u00ean \u0111\u1ebfn kho\u1ea3ng 826 mm\u00b2, theo d\u1eef li\u1ec7u t\u1eeb TechPowerUp. Quy m\u00f4 n\u00e0y cho ph\u00e9p t\u00edch h\u1ee3p s\u1ed1 l\u01b0\u1ee3ng l\u1edbn \u0111\u01a1n v\u1ecb x\u1eed l\u00fd song song, ph\u1ee5c v\u1ee5 c\u00e1c b\u00e0i to\u00e1n AI v\u00e0 HPC.<\/p>\n

B\u00ean trong GPU g\u1ed3m 108 Streaming Multiprocessors, t\u01b0\u01a1ng \u1ee9ng v\u1edbi 6.912 CUDA cores v\u00e0 432 Tensor Cores th\u1ebf h\u1ec7 th\u1ee9 ba. \u0110\u00e2y l\u00e0 n\u1ec1n t\u1ea3ng \u0111\u1ec3 A100 x\u1eed l\u00fd c\u00e1c ph\u00e9p to\u00e1n ma tr\u1eadn v\u1edbi hi\u1ec7u su\u1ea5t r\u1ea5t cao, \u0111\u1eb7c bi\u1ec7t trong deep learning.<\/p>\n

So s\u00e1nh A100 SXM4 v\u00e0 A100 PCIe<\/h2>\n

NVIDIA A100 c\u00f3 2 phi\u00ean b\u1ea3n ch\u00ednh l\u00e0 A100 SXM v\u00e0 A100 PCIe. M\u1eb7c d\u00f9 c\u00f9ng s\u1eed d\u1ee5ng GPU GA100 v\u00e0 dung l\u01b0\u1ee3ng 80GB, phi\u00ean b\u1ea3n SXM4 mang l\u1ea1i hi\u1ec7u n\u0103ng cao h\u01a1n \u0111\u00e1ng k\u1ec3 so v\u1edbi PCIe.<\/p>\n

TF32 tr\u00ean SXM4 \u0111\u1ea1t kho\u1ea3ng 312 TFLOPS, trong khi PCIe ch\u1ec9 kho\u1ea3ng 156 TFLOPS. T\u01b0\u01a1ng t\u1ef1, hi\u1ec7u n\u0103ng FP16 Tensor tr\u00ean SXM4 c\u00f3 th\u1ec3 \u0111\u1ea1t 624 TFLOPS, g\u1ea7n g\u1ea5p \u0111\u00f4i so v\u1edbi b\u1ea3n PCIe.<\/p>\n

Nguy\u00ean nh\u00e2n ch\u00ednh \u0111\u1ebfn t\u1eeb m\u1ee9c TDP cao h\u01a1n, kh\u1ea3 n\u0103ng duy tr\u00ec xung nh\u1ecbp \u1ed5n \u0111\u1ecbnh v\u00e0 \u0111\u1eb7c bi\u1ec7t l\u00e0 h\u1ec7 th\u1ed1ng k\u1ebft n\u1ed1i NVLink tr\u1ef1c ti\u1ebfp, gi\u00fap gi\u1ea3m \u0111\u1ed9 tr\u1ec5 v\u00e0 t\u0103ng throughput gi\u1eefa c\u00e1c GPU.<\/p>\n

\"So<\/a><\/p>\n

Ph\u00e2n t\u00edch t\u1eebng th\u00f4ng s\u1ed1 c\u1ea5u h\u00ecnh NVIDIA A100 SXM4 80GB<\/h2>\n

Hi\u1ec7u n\u0103ng x\u1eed l\u00fd v\u00e0 compute<\/h3>\n

A100 SXM4 80GB \u0111\u1ea1t hi\u1ec7u n\u0103ng t\u00ednh to\u00e1n \u1edf m\u1ee9c r\u1ea5t cao, \u0111\u1eb7c bi\u1ec7t khi s\u1eed d\u1ee5ng Tensor Core.<\/p>\n

Theo th\u00f4ng tin t\u1eeb NVIDIA, GPU n\u00e0y cung c\u1ea5p kho\u1ea3ng 9.7 TFLOPS cho FP64 v\u00e0 19.5 TFLOPS cho FP32. V\u1edbi c\u00e1c workload AI, TF32 \u0111\u1ea1t kho\u1ea3ng 312 TFLOPS, trong khi FP16 Tensor c\u00f3 th\u1ec3 l\u00ean t\u1edbi 624 TFLOPS v\u00e0 INT8 \u0111\u1ea1t kho\u1ea3ng 1248 TOPS.<\/p>\n

\u0110i\u1ec3m \u0111\u00e1ng ch\u00fa \u00fd l\u00e0 TF32 \u0111\u01b0\u1ee3c NVIDIA thi\u1ebft k\u1ebf \u0111\u1ec3 c\u00e2n b\u1eb1ng gi\u1eefa t\u1ed1c \u0111\u1ed9 v\u00e0 \u0111\u1ed9 ch\u00ednh x\u00e1c, gi\u00fap t\u0103ng t\u1ed1c training m\u00e0 kh\u00f4ng c\u1ea7n ch\u1ec9nh s\u1eeda qu\u00e1 nhi\u1ec1u code t\u1eeb FP32 truy\u1ec1n th\u1ed1ng.<\/p>\n

>>> Xem th\u00eam Nh\u1eefng \u0111i\u1ec1u c\u1ea7n l\u01b0u \u00fd tr\u01b0\u1edbc khi mua NVIDIA GPU A100<\/a><\/strong><\/p>\n

B\u1ed9 nh\u1edb HBM2e v\u00e0 b\u0103ng th\u00f4ng<\/h3>\n

A100 SXM4 80GB s\u1eed d\u1ee5ng b\u1ed9 nh\u1edb HBM2e v\u1edbi dung l\u01b0\u1ee3ng 80GB, bus 5120-bit v\u00e0 b\u0103ng th\u00f4ng \u0111\u1ea1t kho\u1ea3ng 2.039 TB\/s theo th\u00f4ng s\u1ed1 t\u1eeb NVIDIA.<\/p>\n

\u0110\u00e2y l\u00e0 m\u1ed9t trong nh\u1eefng y\u1ebfu t\u1ed1 quan tr\u1ecdng nh\u1ea5t quy\u1ebft \u0111\u1ecbnh hi\u1ec7u n\u0103ng th\u1ef1c t\u1ebf. Trong c\u00e1c m\u00f4 h\u00ecnh AI l\u1edbn, t\u1ed1c \u0111\u1ed9 truy xu\u1ea5t d\u1eef li\u1ec7u th\u01b0\u1eddng l\u00e0 \u0111i\u1ec3m ngh\u1ebdn. V\u1edbi m\u1ee9c b\u0103ng th\u00f4ng v\u01b0\u1ee3t 2TB\/s, GPU c\u00f3 th\u1ec3 duy tr\u00ec d\u00f2ng d\u1eef li\u1ec7u li\u00ean t\u1ee5c \u0111\u1ebfn Tensor Core, gi\u00fap t\u1ed1i \u01b0u hi\u1ec7u su\u1ea5t training.<\/p>\n

So v\u1edbi nhi\u1ec1u GPU kh\u00e1c, l\u1ee3i th\u1ebf n\u00e0y gi\u00fap A100 SXM4 x\u1eed l\u00fd t\u1ed1t c\u00e1c m\u00f4 h\u00ecnh c\u00f3 k\u00edch th\u01b0\u1edbc l\u1edbn v\u00e0 batch size cao.<\/p>\n

Xung nh\u1ecbp v\u00e0 b\u1ed9 nh\u1edb \u0111\u1ec7m<\/h3>\n

A100 SXM4 ho\u1ea1t \u0111\u1ed9ng v\u1edbi xung c\u01a1 b\u1ea3n kho\u1ea3ng 1275 MHz v\u00e0 c\u00f3 th\u1ec3 boost l\u00ean kho\u1ea3ng 1410 MHz. Ngo\u00e0i ra, GPU \u0111\u01b0\u1ee3c trang b\u1ecb 40MB L2 cache, theo d\u1eef li\u1ec7u t\u1eeb TechPowerUp.<\/p>\n

Dung l\u01b0\u1ee3ng cache l\u1edbn gi\u00fap gi\u1ea3m s\u1ed1 l\u1ea7n truy c\u1eadp b\u1ed9 nh\u1edb ngo\u00e0i, t\u1eeb \u0111\u00f3 gi\u1ea3m \u0111\u1ed9 tr\u1ec5 v\u00e0 t\u0103ng hi\u1ec7u qu\u1ea3 x\u1eed l\u00fd trong c\u00e1c t\u00e1c v\u1ee5 y\u00eau c\u1ea7u truy xu\u1ea5t d\u1eef li\u1ec7u li\u00ean t\u1ee5c.<\/p>\n

C\u00f4ng su\u1ea5t v\u00e0 thi\u1ebft k\u1ebf ph\u1ea7n c\u1ee9ng<\/h3>\n

GPU c\u00f3 m\u1ee9c TDP kho\u1ea3ng 400W, cao h\u01a1n \u0111\u00e1ng k\u1ec3 so v\u1edbi phi\u00ean b\u1ea3n PCIe. Thi\u1ebft k\u1ebf SXM4 cho ph\u00e9p c\u1ea5p \u0111i\u1ec7n tr\u1ef1c ti\u1ebfp t\u1eeb mainboard server v\u00e0 s\u1eed d\u1ee5ng h\u1ec7 th\u1ed1ng l\u00e0m m\u00e1t chuy\u00ean d\u1ee5ng.<\/p>\n

A100 SXM4 kh\u00f4ng c\u00f3 c\u1ed5ng xu\u1ea5t h\u00ecnh v\u00e0 kh\u00f4ng s\u1eed d\u1ee5ng \u0111\u1ea7u c\u1ea5p ngu\u1ed3n truy\u1ec1n th\u1ed1ng, v\u00ec m\u1ee5c ti\u00eau duy nh\u1ea5t c\u1ee7a n\u00f3 l\u00e0 t\u00ednh to\u00e1n trong data center. Thi\u1ebft k\u1ebf n\u00e0y gi\u00fap t\u1ed1i \u01b0u h\u00f3a m\u1eadt \u0111\u1ed9 compute tr\u00ean m\u1ed7i rack server.<\/p>\n

NVLink v\u00e0 kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng h\u1ec7 th\u1ed1ng<\/h3>\n

M\u1ed9t trong nh\u1eefng \u0111i\u1ec3m m\u1ea1nh l\u1edbn nh\u1ea5t c\u1ee7a A100 SXM4 l\u00e0 h\u1ed7 tr\u1ee3 NVLink v\u1edbi b\u0103ng th\u00f4ng l\u00ean \u0111\u1ebfn kho\u1ea3ng 600 GB\/s, theo NVIDIA.<\/p>\n

C\u00f4ng ngh\u1ec7 n\u00e0y cho ph\u00e9p k\u1ebft n\u1ed1i nhi\u1ec1u GPU l\u1ea1i v\u1edbi nhau nh\u01b0 m\u1ed9t h\u1ec7 th\u1ed1ng th\u1ed1ng nh\u1ea5t. Trong c\u00e1c h\u1ec7 th\u1ed1ng HGX, c\u00f3 th\u1ec3 tri\u1ec3n khai t\u1eeb 4 \u0111\u1ebfn 16 GPU A100 SXM4 ho\u1ea1t \u0111\u1ed9ng song song.<\/p>\n

\u0110i\u1ec1u n\u00e0y \u0111\u1eb7c bi\u1ec7t quan tr\u1ecdng khi training c\u00e1c m\u00f4 h\u00ecnh AI l\u1edbn, n\u01a1i d\u1eef li\u1ec7u v\u00e0 tham s\u1ed1 ph\u1ea3i \u0111\u01b0\u1ee3c chia s\u1ebb li\u00ean t\u1ee5c gi\u1eefa nhi\u1ec1u GPU.<\/p>\n

\"C\u00e1c<\/a>

C\u00e1c th\u1ebf h\u1ec7 NVlink qua t\u1eebng n\u0103m<\/p><\/div>\n

C\u00f4ng ngh\u1ec7 Multi-Instance GPU (MIG)<\/h3>\n

A100 h\u1ed7 tr\u1ee3 t\u00ednh n\u0103ng MIG, cho ph\u00e9p chia m\u1ed9t GPU th\u00e0nh t\u1ed1i \u0111a 7 instance \u0111\u1ed9c l\u1eadp.<\/p>\n

M\u1ed7i instance c\u00f3 t\u00e0i nguy\u00ean ri\u00eang v\u1ec1 compute v\u00e0 b\u1ed9 nh\u1edb, gi\u00fap nhi\u1ec1u workload c\u00f3 th\u1ec3 ch\u1ea1y song song tr\u00ean c\u00f9ng m\u1ed9t GPU m\u00e0 kh\u00f4ng \u1ea3nh h\u01b0\u1edfng l\u1eabn nhau. \u0110\u00e2y l\u00e0 t\u00ednh n\u0103ng r\u1ea5t quan tr\u1ecdng trong m\u00f4i tr\u01b0\u1eddng cloud ho\u1eb7c doanh nghi\u1ec7p c\u1ea7n t\u1ed1i \u01b0u chi ph\u00ed.<\/p>\n

Vai tr\u00f2 th\u1ef1c t\u1ebf trong h\u1ec7 th\u1ed1ng AI<\/h2>\n

A100 SXM4 th\u01b0\u1eddng \u0111\u01b0\u1ee3c tri\u1ec3n khai trong c\u00e1c h\u1ec7 th\u1ed1ng nh\u01b0 NVIDIA DGX A100 ho\u1eb7c HGX A100. \u0110\u00e2y l\u00e0 n\u1ec1n t\u1ea3ng cho nhi\u1ec1u workload quan tr\u1ecdng nh\u01b0 training m\u00f4 h\u00ecnh ng\u00f4n ng\u1eef l\u1edbn, x\u1eed l\u00fd d\u1eef li\u1ec7u quy m\u00f4 l\u1edbn v\u00e0 m\u00f4 ph\u1ecfng khoa h\u1ecdc.<\/p>\n

Theo NVIDIA, A100 c\u00f3 th\u1ec3 mang l\u1ea1i hi\u1ec7u n\u0103ng cao h\u01a1n t\u1edbi 20 l\u1ea7n so v\u1edbi th\u1ebf h\u1ec7 tr\u01b0\u1edbc trong m\u1ed9t s\u1ed1 t\u00e1c v\u1ee5 AI v\u00e0 HPC.<\/p>\n

Trong th\u1ef1c t\u1ebf, c\u00e1c h\u1ec7 th\u1ed1ng s\u1eed d\u1ee5ng A100 SXM4 \u0111\u00e3 tr\u1edf th\u00e0nh ti\u00eau chu\u1ea9n cho h\u1ea1 t\u1ea7ng AI trong giai \u0111o\u1ea1n 2020\u20132024, \u0111\u1eb7c bi\u1ec7t tr\u01b0\u1edbc khi th\u1ebf h\u1ec7 Hopper xu\u1ea5t hi\u1ec7n.<\/p>\n

>>> Xem th\u00eam T\u1ed5ng quan v\u1ec1 NVIDIA GTC 2026: T\u1ea5t c\u1ea3 nh\u1eefng g\u00ec b\u1ea1n c\u1ea7n bi\u1ebft<\/a><\/strong><\/p>\n

T\u1ed5ng k\u1ebft v\u1ec1 NVIDIA A100 SXM4 80GB<\/h2>\n

NVIDIA A100 SXM4 80GB l\u00e0 GPU data center \u0111\u01b0\u1ee3c t\u1ed1i \u01b0u to\u00e0n di\u1ec7n cho AI v\u00e0 HPC, v\u1edbi b\u0103ng th\u00f4ng b\u1ed9 nh\u1edb v\u01b0\u1ee3t 2 TB\/s, hi\u1ec7u n\u0103ng Tensor l\u00ean \u0111\u1ebfn 624 TFLOPS v\u00e0 kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng m\u1ea1nh m\u1ebd th\u00f4ng qua NVLink.<\/p>\n

Gi\u00e1 tr\u1ecb c\u1ed1t l\u00f5i c\u1ee7a A100 SXM4 kh\u00f4ng ch\u1ec9 n\u1eb1m \u1edf th\u00f4ng s\u1ed1 ph\u1ea7n c\u1ee9ng m\u00e0 \u1edf kh\u1ea3 n\u0103ng duy tr\u00ec hi\u1ec7u su\u1ea5t \u1ed5n \u0111\u1ecbnh trong c\u00e1c h\u1ec7 th\u1ed1ng multi-GPU, n\u01a1i m\u00e0 t\u1ed1c \u0111\u1ed9 x\u1eed l\u00fd v\u00e0 kh\u1ea3 n\u0103ng scale quy\u1ebft \u0111\u1ecbnh tr\u1ef1c ti\u1ebfp \u0111\u1ebfn hi\u1ec7u qu\u1ea3 tri\u1ec3n khai AI trong th\u1ef1c t\u1ebf.<\/p>\n

Tri\u1ec3n khai NVIDIA A100 ngay m\u00e0 kh\u00f4ng c\u1ea7n \u0111\u1ea7u t\u01b0 h\u1ea1 t\u1ea7ng<\/h3>\n

B\u1eaft \u0111\u1ea7u v\u1edbi Cloud GPU s\u1eed d\u1ee5ng NVIDIA A100 ch\u1ec9 t\u1eeb 59.000\u0111\/gi\u1edd<\/a> t\u1ea1i VNSO<\/span><\/span>. Kh\u1edfi t\u1ea1o nhanh, s\u1eb5n s\u00e0ng cho training AI, inference v\u00e0 workload HPC m\u00e0 kh\u00f4ng c\u1ea7n \u0111\u1ea7u t\u01b0 server hay v\u1eadn h\u00e0nh ph\u1ee9c t\u1ea1p. \u0110\u0103ng k\u00fd t\u1ef1 \u0111\u1ed9ng\u00a0t\u1ea1i: https:\/\/vnso.vn\/thue-nvidia-a100\/<\/strong><\/p>\n

N\u1ebfu c\u1ea7n hi\u1ec7u n\u0103ng cao v\u00e0 h\u1ec7 th\u1ed1ng ri\u00eang, VNSO cung c\u1ea5p Server GPU v\u1edbi \u0111\u1ea7y \u0111\u1ee7 d\u00f2ng NVIDIA<\/span><\/span> ph\u1ee5c v\u1ee5 AI nh\u01b0 A100, H100, RTX series, t\u1ed1i \u01b0u cho doanh nghi\u1ec7p tri\u1ec3n khai l\u00e2u d\u00e0i.<\/p>\n

Li\u00ean h\u1ec7 VNSO \u0111\u1ec3 \u0111\u01b0\u1ee3c t\u01b0 v\u1ea5n c\u1ea5u h\u00ecnh ph\u00f9 h\u1ee3p v\u00e0 tri\u1ec3n khai nhanh theo nhu c\u1ea7u th\u1ef1c t\u1ebf.<\/strong><\/p>\n

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