{"id":22887,"date":"2025-10-24T08:09:05","date_gmt":"2025-10-24T01:09:05","guid":{"rendered":"https:\/\/thegioimaychu.vn\/blog\/?p=22887"},"modified":"2025-10-24T08:19:12","modified_gmt":"2025-10-24T01:19:12","slug":"tai-sao-goi-nvidia-dgx-spark-la-sieu-may-tinh-ai-ca-nhan","status":"publish","type":"post","link":"https:\/\/thegioimaychu.vn\/blog\/ai-hpc\/tai-sao-goi-nvidia-dgx-spark-la-sieu-may-tinh-ai-ca-nhan-p22887\/","title":{"rendered":"T\u1ea1i sao g\u1ecdi NVIDIA DGX Spark l\u00e0 Si\u00eau m\u00e1y t\u00ednh AI c\u00e1 nh\u00e2n?"},"content":{"rendered":"<style>.iblink{color:#975!important;}.iblink:hover{color:orange!important;}<\/style><p>Vi\u1ec7c ra m\u1eaft th\u1ebf h\u1ec7 m\u00e1y t\u00ednh NVIDIA <a class=\"iblink\" href=\"\/blog\/tag\/dgxspark\/\">DGX Spark<\/a> \u0111\u00e1nh d\u1ea5u m\u1ed9t b\u01b0\u1edbc ngo\u1eb7t l\u1edbn c\u1ee7a ri\u00eang NVIDIA l\u1eabn c\u1ea3 ng\u00e0nh c\u00f4ng nghi\u1ec7p AI, \u0111\u01b0a s\u1ee9c m\u1ea1nh t\u00ednh to\u00e1n c\u1ea5p \u0111\u1ed9 trung t\u00e2m d\u1eef li\u1ec7u (Data Center) xu\u1ed1ng ngay b\u00e0n l\u00e0m vi\u1ec7c c\u1ee7a c\u00e1c nh\u00e0 ph\u00e1t tri\u1ec3n. N\u00f3 \u0111\u01b0\u1ee3c g\u1ecdi l\u00e0 &#8220;si\u00eau m\u00e1y t\u00ednh&#8221; AI c\u00e1 nh\u00e2n l\u00e0 c\u00f3 l\u00fd do c\u1ee7a n\u00f3. Trong khi c\u00e1c PC th\u00f4ng th\u01b0\u1eddng (th\u1eadm ch\u00ed l\u00e0 c\u00e1c m\u00e1y tr\u1ea1m cao c\u1ea5p) v\u1eabn d\u1ef1a tr\u00ean ki\u1ebfn tr\u00fac m\u00e1y t\u00ednh truy\u1ec1n th\u1ed1ng, <a class=\"iblink\" href=\"\/blog\/tag\/dgxspark\/\">DGX Spark<\/a> \u0111\u01b0\u1ee3c\u00a0<b>thi\u1ebft k\u1ebf l\u1ea1i t\u1eeb \u0111\u1ea7u \u0111\u1ec3 t\u1ed1i \u01b0u h\u00f3a tri\u1ec7t \u0111\u1ec3 cho AI v\u00e0 h\u1ecdc s\u00e2u (<a class=\"iblink\" href=\"\/blog\/tag\/deep-learning\/\">Deep Learning<\/a>)<\/b>. S\u1ef1 kh\u00e1c bi\u1ec7t n\u00e0y kh\u00f4ng ch\u1ec9 n\u1eb1m \u1edf s\u1ed1 l\u01b0\u1ee3ng nh\u00e2n GPU, m\u00e0 \u1edf m\u1ed9t ki\u1ebfn tr\u00fac t\u00edch h\u1ee3p s\u00e2u, m\u1ed9t h\u1ec7 sinh th\u00e1i ph\u1ea7n m\u1ec1m ho\u00e0n ch\u1ec9nh v\u00e0 hi\u1ec7u qu\u1ea3 n\u0103ng l\u01b0\u1ee3ng v\u01b0\u1ee3t tr\u1ed9i.<\/p>\n<h2>Ki\u1ebfn tr\u00fac ph\u1ea7n c\u1ee9ng: S\u1ef1 t\u00edch h\u1ee3p c\u1ee7a ki\u1ebfn tr\u00fac Grace Blackwell\u00a0v\u01b0\u1ee3t tr\u1ed9i<\/h2>\n<p>S\u1ef1 kh\u00e1c bi\u1ec7t c\u1ed1t l\u00f5i nh\u1ea5t n\u1eb1m \u1edf &#8220;tr\u00e1i tim&#8221; c\u1ee7a DGX Spark:\u00a0<b>Si\u00eau chip NVIDIA GB10 Grace Blackwell<\/b>. \u0110\u00e2y l\u00e0 m\u1ed9t c\u00e1ch ti\u1ebfp c\u1eadn ho\u00e0n to\u00e0n kh\u00e1c bi\u1ec7t so v\u1edbi vi\u1ec7c l\u1eafp r\u00e1p CPU v\u00e0 GPU v\u00e0o c\u00f9ng m\u1ed9t bo m\u1ea1ch ch\u1ee7 nh\u01b0 PC th\u00f4ng th\u01b0\u1eddng.<\/p>\n<h3>Si\u00eau chip h\u1ec7 th\u1ed1ng (SoC) so v\u1edbi ki\u1ebfn tr\u00fac r\u1eddi r\u1ea1c (x86)<\/h3>\n<table class=\"table sheet\">\n<thead>\n<tr>\n<td><strong>\u0110\u1eb7c \u0111i\u1ec3m<\/strong><\/td>\n<td><strong>NVIDIA DGX Spark<\/strong><\/td>\n<td><strong>PC Th\u00f4ng Th\u01b0\u1eddng (K\u1ec3 c\u1ea3 Workstation)<\/strong><\/td>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><b>Linh ki\u1ec7n x\u1eed l\u00fd ch\u00ednh<\/b><\/td>\n<td><b>Si\u00eau chip GB10 Grace Blackwell<\/b>\u00a0(SoC) t\u00edch h\u1ee3p\u00a0<b>CPU Grace<\/b>\u00a0(ki\u1ebfn tr\u00fac Arm Neoverse) v\u00e0\u00a0<b>GPU Blackwell<\/b>\u00a0v\u00e0o c\u00f9ng m\u1ed9t g\u00f3i v\u1eadt l\u00fd.<\/td>\n<td>CPU (ki\u1ebfn tr\u00fac x86, nh\u01b0 Intel\/AMD) v\u00e0 GPU (nh\u01b0 NVIDIA GeForce\/RTX Pro) l\u00e0 c\u00e1c chip r\u1eddi r\u1ea1c.<\/td>\n<\/tr>\n<tr>\n<td><b>Giao ti\u1ebfp CPU-GPU<\/b><\/td>\n<td>C\u00f4ng ngh\u1ec7\u00a0<b>NVLink-C2C<\/b>\u00a0(Chip-to-Chip), cung c\u1ea5p b\u0103ng th\u00f4ng c\u1ef1c cao, \u0111\u1ed9 tr\u1ec5 c\u1ef1c th\u1ea5p.<\/td>\n<td>Bus\u00a0<b>PCIe Gen 5<\/b>\u00a0ho\u1eb7c c\u0169 h\u01a1n.<\/td>\n<\/tr>\n<tr>\n<td><b>T\u1ed1c \u0111\u1ed9 truy\u1ec1n d\u1eef li\u1ec7u<\/b><\/td>\n<td>L\u00ean \u0111\u1ebfn h\u00e0ng tr\u0103m GB\/s (th\u00f4ng qua NVLink-C2C), lo\u1ea1i b\u1ecf h\u1ea7u h\u1ebft c\u00e1c n\u00fat th\u1eaft c\u1ed5 chai.<\/td>\n<td>Gi\u1edbi h\u1ea1n b\u1edfi b\u0103ng th\u00f4ng PCIe (v\u00ed d\u1ee5: PCIe 5.0 x16 kho\u1ea3ng\u00a0<span data-math=\"64\">$64$<\/span>\u00a0GB\/s).<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u0110i\u1ec3m m\u1ea5u ch\u1ed1t \u1edf \u0111\u00e2y \u0111\u00f3 l\u00e0,\u00a0vi\u1ec7c s\u1eed d\u1ee5ng NVLink-C2C cho ph\u00e9p CPU v\u00e0 GPU ho\u1ea1t \u0111\u1ed9ng g\u1ea7n nh\u01b0 l\u00e0 m\u1ed9t \u0111\u01a1n v\u1ecb x\u1eed l\u00fd duy nh\u1ea5t. Trong c\u00e1c t\u00e1c v\u1ee5 AI, lu\u1ed3ng d\u1eef li\u1ec7u li\u00ean t\u1ee5c chuy\u1ec3n \u0111\u1ed5i gi\u1eefa x\u1eed l\u00fd tu\u1ea7n t\u1ef1 (CPU) v\u00e0 x\u1eed l\u00fd song song (GPU). \u0110\u1ed9 tr\u1ec5 c\u1ef1c th\u1ea5p v\u00e0 b\u0103ng th\u00f4ng l\u1edbn c\u1ee7a NVLink-C2C gi\u00fap\u00a0<b>t\u0103ng t\u1ed1c \u0111\u1ed9 l\u1eb7p (iteration) trong hu\u1ea5n luy\u1ec7n m\u00f4 h\u00ecnh<\/b>\u00a0l\u00ean m\u1ee9c \u0111\u1ed9t ph\u00e1, \u0111i\u1ec1u m\u00e0 PCIe, cho d\u00f9 l\u00e0 th\u1ebf h\u1ec7 m\u1edbi nh\u1ea5t (Gen 5), c\u0169ng kh\u00f4ng th\u1ec3 b\u1eaft k\u1ecbp.<\/p>\n<h3>B\u1ed9 nh\u1edb h\u1ee3p nh\u1ea5t (Unified Memory)<\/h3>\n<p>DGX Spark \u0111\u01b0\u1ee3c trang b\u1ecb\u00a0<b>128GB b\u1ed9 nh\u1edb LPDDR5X b\u0103ng th\u00f4ng cao<\/b>\u00a0ho\u1ea1t \u0111\u1ed9ng nh\u01b0 m\u1ed9t\u00a0<b>v\u00f9ng nh\u1edb h\u1ee3p nh\u1ea5t<\/b>\u00a0(Unified Memory), c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c truy c\u1eadp \u0111\u1ed3ng th\u1eddi b\u1edfi c\u1ea3 CPU Grace v\u00e0 GPU Blackwell.<\/p>\n<ul>\n<li><b>PC th\u00f4ng th\u01b0\u1eddng:<\/b>\u00a0CPU s\u1eed d\u1ee5ng RAM DDR, GPU s\u1eed d\u1ee5ng VRAM (GDDR). D\u1eef li\u1ec7u c\u1ea7n ph\u1ea3i \u0111\u01b0\u1ee3c sao ch\u00e9p (copy) qua l\u1ea1i gi\u1eefa hai v\u00f9ng nh\u1edb n\u00e0y <strong>qua bus PCIe<\/strong>, g\u00e2y\u00a0<b>t\u1ed1n th\u1eddi gian v\u00e0 l\u00e3ng ph\u00ed chu k\u1ef3 t\u00ednh to\u00e1n<\/b>\u00a0(compute cycle).<\/li>\n<li><b>DGX Spark:<\/b>\u00a0V\u1edbi b\u1ed9 nh\u1edb h\u1ee3p nh\u1ea5t, vi\u1ec7c chuy\u1ec3n d\u1eef li\u1ec7u l\u1edbn cho c\u00e1c m\u00f4 h\u00ecnh ng\u00f4n ng\u1eef l\u1edbn (<b>LLM<\/b>) ho\u1eb7c m\u00f4 h\u00ecnh sinh t\u1ea1o (Generative AI) tr\u1edf n\u00ean\u00a0<b>t\u1ee9c th\u1eddi v\u00e0 li\u1ec1n m\u1ea1ch<\/b>. \u0110i\u1ec1u n\u00e0y cho ph\u00e9p DGX Spark c\u00f3 kh\u1ea3 n\u0103ng ch\u1ea1y suy lu\u1eadn (inference) tr\u00ean c\u00e1c m\u00f4 h\u00ecnh l\u00ean \u0111\u1ebfn\u00a0<b>200 t\u1ef7 tham s\u1ed1<\/b>\u00a0v\u00e0 tinh ch\u1ec9nh (fine-tune) c\u00e1c m\u00f4 h\u00ecnh\u00a0<span data-math=\"70\">70<\/span>\u00a0t\u1ef7 tham s\u1ed1 ngay t\u1ea1i ch\u1ed7 \u2013 m\u1ed9t nhi\u1ec7m v\u1ee5 b\u1ea5t kh\u1ea3 thi \u0111\u1ed1i v\u1edbi h\u1ea7u h\u1ebft c\u00e1c PC truy\u1ec1n th\u1ed1ng.<\/li>\n<\/ul>\n<h2>Hi\u1ec7u n\u0103ng t\u00ednh to\u00e1n t\u1ed1i \u01b0u cho AI<\/h2>\n<p>DGX Spark kh\u00f4ng ch\u1ec9 m\u1ea1nh v\u1ec1 t\u1ed1c \u0111\u1ed9 truy\u1ec1n d\u1eef li\u1ec7u m\u00e0 c\u00f2n v\u1ec1 c\u00e1ch n\u00f3 th\u1ef1c hi\u1ec7n c\u00e1c ph\u00e9p t\u00ednh.<\/p>\n<h3>Tensor Core v\u00e0 \u0111\u1ed9 ch\u00ednh x\u00e1c th\u1ea5p (FP4)<\/h3>\n<p>GPU Blackwell trong DGX Spark \u0111\u01b0\u1ee3c trang b\u1ecb\u00a0<b>Nh\u00e2n Tensor (Tensor Core)<\/b>\u00a0th\u1ebf h\u1ec7 m\u1edbi nh\u1ea5t. C\u00e1c nh\u00e2n n\u00e0y \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf \u0111\u1eb7c bi\u1ec7t \u0111\u1ec3 t\u0103ng t\u1ed1c c\u00e1c ph\u00e9p to\u00e1n ma tr\u1eadn, c\u1ed1t l\u00f5i c\u1ee7a h\u1ecdc s\u00e2u.<\/p>\n<ul>\n<li><b>Hi\u1ec7u n\u0103ng PetaFLOP AI:<\/b>\u00a0DGX Spark c\u00f3 th\u1ec3 \u0111\u1ea1t t\u1edbi\u00a0<b>1.000 AI TOPS<\/b>\u00a0(t\u1ee9c\u00a0<b>1 PetaFLOP<\/b>\u00a0\u1edf \u0111\u1ed9 ch\u00ednh x\u00e1c FP4).<\/li>\n<li><b>\u0110\u1ed9 ch\u00ednh x\u00e1c chuy\u00ean d\u1ee5ng:<\/b>\u00a0DGX Spark khai th\u00e1c t\u1ed1i \u0111a \u0111\u1ed9 ch\u00ednh x\u00e1c th\u1ea5p nh\u01b0\u00a0<b>FP4<\/b>\u00a0(4-bit Floating Point) v\u00e0\u00a0<b>FP8<\/b>\u00a0(8-bit Floating Point). C\u00e1c m\u00f4 h\u00ecnh AI hi\u1ec7n \u0111\u1ea1i \u0111\u00e3 \u0111\u01b0\u1ee3c ch\u1ee9ng minh l\u00e0 c\u00f3 th\u1ec3 hu\u1ea5n luy\u1ec7n v\u00e0 suy lu\u1eadn hi\u1ec7u qu\u1ea3 v\u1edbi \u0111\u1ed9 ch\u00ednh x\u00e1c th\u1ea5p h\u01a1n, gi\u00fap\u00a0<b>gi\u1ea3m\u00a0<span data-math=\"4-8\">4-8<\/span>\u00a0l\u1ea7n nhu c\u1ea7u b\u1ed9 nh\u1edb v\u00e0 t\u0103ng th\u00f4ng l\u01b0\u1ee3ng t\u00ednh to\u00e1n<\/b>\u00a0so v\u1edbi c\u00e1c \u0111\u1ecbnh d\u1ea1ng truy\u1ec1n th\u1ed1ng (nh\u01b0 FP32) m\u00e0 PC th\u00f4ng th\u01b0\u1eddng th\u01b0\u1eddng s\u1eed d\u1ee5ng.<\/li>\n<\/ul>\n<h3>Hi\u1ec7u qu\u1ea3 s\u1eed d\u1ee5ng n\u0103ng l\u01b0\u1ee3ng v\u00e0 m\u1eadt \u0111\u1ed9 t\u00ednh to\u00e1n<\/h3>\n<p>DGX Spark \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf \u0111\u1ec3 mang l\u1ea1i hi\u1ec7u n\u0103ng si\u00eau m\u00e1y t\u00ednh trong m\u1ed9t khung m\u00e1y nh\u1ecf g\u1ecdn, ti\u00eau th\u1ee5 \u0111i\u1ec7n n\u0103ng ch\u1ec9 kho\u1ea3ng\u00a0<b>170W<\/b>\u00a0\u1edf m\u1ee9c t\u1ea3i t\u1ed1i \u0111a.<\/p>\n<ul>\n<li><b>PC\/Workstation:<\/b>\u00a0\u0110\u1ec3 \u0111\u1ea1t \u0111\u01b0\u1ee3c hi\u1ec7u n\u0103ng t\u01b0\u01a1ng \u0111\u01b0\u01a1ng, m\u1ed9t PC Workstation th\u00f4ng th\u01b0\u1eddng s\u1ebd c\u1ea7n nhi\u1ec1u GPU, ti\u00eau th\u1ee5 h\u00e0ng ngh\u00ecn Watt \u0111i\u1ec7n, t\u1ecfa nhi\u1ec7t l\u1edbn v\u00e0 c\u1ea7n h\u1ec7 th\u1ed1ng l\u00e0m m\u00e1t ph\u1ee9c t\u1ea1p.<\/li>\n<li><b>DGX Spark:<\/b>\u00a0Nh\u1edd ki\u1ebfn tr\u00fac Grace Arm ti\u1ebft ki\u1ec7m \u0111i\u1ec7n v\u00e0 t\u00edch h\u1ee3p ch\u1eb7t ch\u1ebd, DGX Spark \u0111\u1ea1t \u0111\u01b0\u1ee3c\u00a0<b>m\u1eadt \u0111\u1ed9 t\u00ednh to\u00e1n (compute density) c\u1ef1c cao<\/b>\u00a0v\u1edbi m\u1ee9c ti\u00eau th\u1ee5 \u0111i\u1ec7n n\u0103ng t\u1ed1i \u01b0u, l\u00fd t\u01b0\u1edfng cho m\u00f4i tr\u01b0\u1eddng v\u0103n ph\u00f2ng.<\/li>\n<\/ul>\n<h2>H\u1ec7 sinh th\u00e1i ph\u1ea7n m\u1ec1m v\u00e0 kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng<\/h2>\n<p>M\u1ed9t chi\u1ebfc PC m\u1ea1nh ch\u1ec9 l\u00e0 ph\u1ea7n c\u1ee9ng. DGX Spark l\u00e0 m\u1ed9t\u00a0<b>gi\u1ea3i ph\u00e1p AI to\u00e0n di\u1ec7n<\/b>.<\/p>\n<h3>T\u00edch h\u1ee3p s\u1eb5n s\u00e0ng v\u1edbi DGX OS v\u00e0 AI Enterprise<\/h3>\n<p>DGX Spark \u0111\u01b0\u1ee3c c\u00e0i \u0111\u1eb7t s\u1eb5n\u00a0<b>NVIDIA DGX OS<\/b>\u00a0v\u00e0\u00a0<b><a class=\"iblink\" href=\"\/solution\/infra\/ai\/bo-giai-phap-trien-khai-ai-cap-doanh-nghiep-nvidia-ai-enterprise-p4126\/\">NVIDIA AI Enterprise<\/a> Stack<\/b>.<\/p>\n<ul>\n<li><b>Ph\u1ea7n m\u1ec1m t\u1ed1i \u01b0u:<\/b>\u00a0H\u1ec7 \u0111i\u1ec1u h\u00e0nh v\u00e0 c\u00e1c framework AI (CUDA, PyTorch, TensorFlow) \u0111\u00e3 \u0111\u01b0\u1ee3c\u00a0<b>tinh ch\u1ec9nh v\u00e0 ki\u1ec3m ch\u1ee9ng<\/b>\u00a0\u0111\u1ec3 ho\u1ea1t \u0111\u1ed9ng t\u1ed1i \u0111a v\u1edbi ki\u1ebfn tr\u00fac Grace Blackwell. \u0110i\u1ec1u n\u00e0y lo\u1ea1i b\u1ecf c\u00e1c v\u1ea5n \u0111\u1ec1 t\u01b0\u01a1ng th\u00edch, driver, v\u00e0 t\u1ed1i \u01b0u h\u00f3a m\u00e0 c\u00e1c k\u1ef9 s\u01b0 AI th\u01b0\u1eddng g\u1eb7p khi t\u1ef1 x\u00e2y d\u1ef1ng h\u1ec7 th\u1ed1ng tr\u00ean PC.<\/li>\n<li><b>T\u0103ng t\u1ed1c ph\u00e1t tri\u1ec3n:<\/b>\u00a0Cung c\u1ea5p s\u1eb5n c\u00e1c c\u00f4ng c\u1ee5, th\u01b0 vi\u1ec7n nh\u01b0\u00a0<b>NVIDIA RAPIDS<\/b>\u00a0(cho khoa h\u1ecdc d\u1eef li\u1ec7u),\u00a0<b>NVIDIA Isaac<\/b>\u00a0(cho robot) v\u00e0\u00a0<b>NVIDIA Metropolis<\/b>\u00a0(cho <a class=\"iblink\" href=\"\/blog\/tag\/computer-vision\/\">th\u1ecb gi\u00e1c m\u00e1y t\u00ednh<\/a>), cho ph\u00e9p c\u00e1c nh\u00e0 ph\u00e1t tri\u1ec3n t\u1eadp trung v\u00e0o thu\u1eadt to\u00e1n thay v\u00ec t\u1ed1i \u01b0u h\u00f3a h\u1ea1 t\u1ea7ng.<\/li>\n<\/ul>\n<h3>Kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng (scalability) li\u1ec1n m\u1ea1ch<\/h3>\n<p><strong>DGX Spark l\u00e0 \u0111i\u1ec3m kh\u1edfi \u0111\u1ea7u trong h\u1ec7 sinh th\u00e1i DGX.<\/strong> N\u00f3 ch\u1ea1y c\u00f9ng m\u1ed9t ng\u0103n x\u1ebfp ph\u1ea7n m\u1ec1m v\u00e0 ki\u1ebfn tr\u00fac (Arm\/Blackwell) v\u1edbi c\u00e1c si\u00eau m\u00e1y t\u00ednh quy m\u00f4 l\u1edbn h\u01a1n nh\u01b0 NVIDIA DGX Station ho\u1eb7c DGX BasePOD.<\/p>\n<p><b>Chuy\u1ec3n \u0111\u1ed5i li\u1ec1n m\u1ea1ch:<\/b>\u00a0C\u00e1c m\u00f4 h\u00ecnh AI \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n v\u00e0 tinh ch\u1ec9nh tr\u00ean DGX Spark c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c\u00a0<b>tri\u1ec3n khai v\u00e0 m\u1edf r\u1ed9ng quy m\u00f4<\/b>\u00a0l\u00ean c\u00e1c trung t\u00e2m d\u1eef li\u1ec7u DGX l\u1edbn h\u01a1n ho\u1eb7c l\u00ean \u0111\u00e1m m\u00e2y (cloud) m\u00e0 kh\u00f4ng c\u1ea7n vi\u1ebft l\u1ea1i m\u00e3 ho\u1eb7c t\u1ed1i \u01b0u h\u00f3a l\u1ea1i. \u0110i\u1ec1u n\u00e0y l\u00e0 then ch\u1ed1t \u0111\u1ed1i v\u1edbi c\u00e1c doanh nghi\u1ec7p \u0111ang ph\u00e1t tri\u1ec3n AI t\u1eeb ph\u00f2ng th\u00ed nghi\u1ec7m l\u00ean s\u1ea3n xu\u1ea5t. PC th\u00f4ng th\u01b0\u1eddng kh\u00f4ng c\u00f3 s\u1ef1 t\u01b0\u01a1ng th\u00edch ki\u1ebfn tr\u00fac n\u00e0y.<\/p>\n<blockquote><p><img decoding=\"async\" class=\"alignleft\" style=\"max-width: 100%; width: 300px;\" src=\"https:\/\/thegioimaychu.vn\/blog\/wp-content\/uploads\/2025\/10\/tgmc-blog-68fad368149fb.jpg\" alt=\"\" \/><\/p>\n<p>Hi\u1ec7n t\u1ea1i, NVIDIA \u0111\u00e3 b\u1eaft \u0111\u1ea7u cho b\u00e1n ra th\u1ecb tr\u01b0\u1eddng s\u1ea3n ph\u1ea9m n\u00e0y th\u00f4ng qua c\u00e1c nh\u00e0 s\u1ea3n xu\u1ea5t OEM nh\u01b0: <a class=\"iblink\" href=\"\/asus\/\">ASUS<\/a> v\u1edbi model <a href=\"https:\/\/thegioimaychu.vn\/may-tinh-tri-tue-nhan-tao-asus-ascent-gx10-4tb-nvme-pcie-gen-5-bh-3-nam-tang-thiet-bi-nas-tm9982.html\"><strong>Ascent GX10<\/strong><\/a>, MSI v\u1edbi model <a href=\"https:\/\/thegioimaychu.vn\/may-tinh-tri-tue-nhan-tao-msi-edgexpert-ms-c931-4tb-pcie-5-0-bh-03-nam-tang-thiet-bi-nas-tm9978.html\"><strong>EdgeXpert\u00a0MS-C931<\/strong><\/a>, Gigabyte v\u1edbi model <a href=\"https:\/\/thegioimaychu.vn\/may-tinh-tri-tue-nhan-tao-gigabyte-ai-top-atom-tm9984.html\">AI TOP Atom<\/a>,&#8230; T\u1ea5t c\u1ea3 c\u00e1c s\u1ea3n ph\u1ea9m n\u00e0y \u0111\u1ec1u d\u1ef1a tr\u00ean n\u1ec1n t\u1ea3ng c\u1ee7a DGX Spark v\u00e0 s\u1edf h\u1eefu ch\u00ednh x\u00e1c c\u00e1c t\u00ednh n\u0103ng v\u00e0 hi\u1ec7u n\u0103ng h\u1ec7 th\u1ed1ng nh\u01b0 s\u1ea3n ph\u1ea9m <a href=\"https:\/\/thegioimaychu.vn\/may-tinh-tri-tue-nhan-tao-nvidia-dgx-spark-founder-edition-tm9855.html\">DGX Spark Founder Edition<\/a> c\u1ee7a NVIDIA.<\/p><\/blockquote>\n<h2>K\u1ebft lu\u1eadn: T\u1eeb m\u00e1y t\u00ednh \u0111\u1ec3 b\u00e0n \u0111\u1ebfn si\u00eau m\u00e1y t\u00ednh<\/h2>\n<p>NVIDIA DGX Spark kh\u00f4ng ph\u1ea3i l\u00e0 m\u1ed9t chi\u1ebfc PC cao c\u1ea5p; n\u00f3 l\u00e0 m\u1ed9t\u00a0<b>thi\u1ebft b\u1ecb ph\u00e1t tri\u1ec3n AI chuy\u00ean d\u1ee5ng<\/b>. N\u00f3 v\u01b0\u1ee3t tr\u1ed9i so v\u1edbi PC th\u00f4ng th\u01b0\u1eddng nh\u1edd:<\/p>\n<ol start=\"1\">\n<li><b>Ki\u1ebfn tr\u00fac h\u1ee3p nh\u1ea5t:<\/b>\u00a0Si\u00eau chip Grace Blackwell v\u00e0 b\u1ed9 nh\u1edb h\u1ee3p nh\u1ea5t lo\u1ea1i b\u1ecf n\u00fat th\u1eaft c\u1ed5 chai PCIe.<\/li>\n<li><b>Hi\u1ec7u n\u0103ng chuy\u00ean bi\u1ec7t:<\/b>\u00a0Nh\u00e2n Tensor v\u00e0 h\u1ed7 tr\u1ee3 \u0111\u1ed9 ch\u00ednh x\u00e1c FP4\/FP8 mang l\u1ea1i hi\u1ec7u n\u0103ng c\u1ea5p \u0111\u1ed9 PetaFLOP.<\/li>\n<li><b>H\u1ec7 sinh th\u00e1i to\u00e0n di\u1ec7n:<\/b>\u00a0Ph\u1ea7n m\u1ec1m t\u1ed1i \u01b0u h\u00f3a DGX OS gi\u00fap c\u00e1c m\u00f4 h\u00ecnh c\u00f3 th\u1ec3 d\u1ec5 d\u00e0ng m\u1edf r\u1ed9ng t\u1eeb b\u00e0n l\u00e0m vi\u1ec7c \u0111\u1ebfn trung t\u00e2m d\u1eef li\u1ec7u.<\/li>\n<\/ol>\n<p>DGX Spark \u0111\u1ecbnh h\u00ecnh l\u1ea1i c\u00e1ch c\u00e1c k\u1ef9 s\u01b0 AI ti\u1ebfp c\u1eadn s\u1ee9c m\u1ea1nh t\u00ednh to\u00e1n, bi\u1ebfn AI quy m\u00f4 l\u1edbn tr\u1edf n\u00ean d\u1ec5 ti\u1ebfp c\u1eadn, ri\u00eang t\u01b0 v\u00e0 hi\u1ec7u qu\u1ea3 h\u01a1n bao gi\u1edd h\u1ebft.<\/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=23395\">\u0110\u00e1nh gi\u00e1 hi\u1ec7u n\u0103ng c\u1ee7a c\u00e1c AI Agent c\u1ee5c b\u1ed9 tr\u00ean NVIDIA DGX Spark (Ollama + OpenClaw)<\/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<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Vi&#7879;c ra m&#7855;t th&#7871; h&#7879; m&aacute;y t&iacute;nh NVIDIA DGX Spark &#273;&aacute;nh d&#7845;u m&#7897;t b&#432;&#7899;c ngo&#7863;t l&#7899;n c&#7911;a ri&ecirc;ng NVIDIA l&#7851;n c&#7843; ng&agrave;nh c&ocirc;ng nghi&#7879;p AI, &#273;&#432;a s&#7913;c m&#7841;nh t&iacute;nh to&aacute;n c&#7845;p &#273;&#7897; trung t&acirc;m d&#7919; li&#7879;u (Data Center) xu&#7889;ng ngay b&agrave;n l&agrave;m vi&#7879;c c&#7911;a c&aacute;c nh&agrave; ph&aacute;t tri&#7875;n. N&oacute; &#273;&#432;&#7907;c g&#7885;i l&agrave; &ldquo;si&ecirc;u m&aacute;y t&iacute;nh&rdquo;&#8230;<\/p>\n","protected":false},"author":2,"featured_media":22889,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[3,1],"tags":[1362,1314],"class_list":["post-22887","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-hpc","category-tong-hop","tag-dgxspark","tag-nvidia"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>T\u1ea1i sao g\u1ecdi NVIDIA DGX Spark l\u00e0 Si\u00eau m\u00e1y t\u00ednh AI c\u00e1 nh\u00e2n? - 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\/tai-sao-goi-nvidia-dgx-spark-la-sieu-may-tinh-ai-ca-nhan-p22887\/\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:title\" content=\"T\u1ea1i sao g\u1ecdi NVIDIA DGX Spark l\u00e0 Si\u00eau m\u00e1y t\u00ednh AI c\u00e1 nh\u00e2n? - Blog | TheGioiMayChu\" \/>\n<meta name=\"twitter:description\" content=\"Vi&#7879;c ra m&#7855;t th&#7871; h&#7879; m&aacute;y t&iacute;nh NVIDIA DGX Spark &#273;&aacute;nh d&#7845;u m&#7897;t b&#432;&#7899;c ngo&#7863;t l&#7899;n c&#7911;a ri&ecirc;ng NVIDIA l&#7851;n c&#7843; ng&agrave;nh c&ocirc;ng nghi&#7879;p AI, &#273;&#432;a s&#7913;c m&#7841;nh t&iacute;nh to&aacute;n c&#7845;p &#273;&#7897; trung t&acirc;m d&#7919; li&#7879;u (Data Center) xu&#7889;ng ngay b&agrave;n l&agrave;m vi&#7879;c c&#7911;a c&aacute;c nh&agrave; ph&aacute;t tri&#7875;n. 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