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public/htmls/AI算力芯片.html
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public/htmls/AI算力芯片.html
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<!DOCTYPE html>
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<html lang="zh-CN" data-theme="night">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>AI算力芯片 - 深度研究报告</title>
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<script src="https://cdn.tailwindcss.com"></script>
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<link href="https://cdn.jsdelivr.net/npm/daisyui@4.11.1/dist/full.min.css" rel="stylesheet" type="text/css" />
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<script defer src="https://cdn.jsdelivr.net/npm/alpinejs@3.x.x/dist/cdn.min.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/echarts@5.5.0/dist/echarts.min.js"></script>
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<link rel="preconnect" href="https://fonts.googleapis.com">
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<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
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<link href="https://fonts.googleapis.com/css2?family=Lexend:wght@300;400;500;600;700&display=swap" rel="stylesheet">
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<style>
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body {
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font-family: 'Lexend', sans-serif;
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background-color: #010008;
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color: #e0e0e0;
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}
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.glass-card {
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background: rgba(15, 23, 42, 0.4); /* slate-900 with opacity */
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backdrop-filter: blur(20px);
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-webkit-backdrop-filter: blur(20px);
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border: 1px solid rgba(56, 189, 248, 0.2); /* sky-400 with opacity */
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transition: all 0.3s ease;
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}
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.glass-card:hover {
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background: rgba(15, 23, 42, 0.6);
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border: 1px solid rgba(56, 189, 248, 0.4);
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box-shadow: 0 0 25px rgba(56, 189, 248, 0.15);
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}
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.glow-text {
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text-shadow: 0 0 8px rgba(96, 165, 250, 0.7); /* blue-400 */
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}
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.glow-text-cyan {
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color: #67e8f9; /* cyan-300 */
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text-shadow: 0 0 10px rgba(34, 211, 238, 0.6); /* cyan-400 */
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}
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.glow-text-fuchsia {
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color: #f0abfc; /* fuchsia-300 */
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text-shadow: 0 0 10px rgba(232, 121, 249, 0.6); /* fuchsia-400 */
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}
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.title-gradient {
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background: linear-gradient(90deg, #a5b4fc, #67e8f9); /* indigo-300 to cyan-300 */
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-webkit-background-clip: text;
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-webkit-text-fill-color: transparent;
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}
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.bento-grid {
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display: grid;
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gap: 1rem;
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grid-template-columns: repeat(12, 1fr);
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}
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.bento-item {
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border-radius: 1.5rem;
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padding: 1.5rem;
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}
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.col-span-12 { grid-column: span 12; }
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.col-span-6 { grid-column: span 6; }
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.col-span-4 { grid-column: span 4; }
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.col-span-8 { grid-column: span 8; }
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@media (max-width: 1024px) {
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.col-span-lg-4 { grid-column: span 6; }
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.col-span-lg-6 { grid-column: span 12; }
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.col-span-lg-8 { grid-column: span 12; }
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}
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@media (max-width: 768px) {
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.col-span-md-12 { grid-column: span 12; }
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}
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.tab-lifted.tab-active {
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background-color: rgba(15, 23, 42, 0.4) !important;
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border-color: rgba(56, 189, 248, 0.2) !important;
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border-bottom-color: transparent !important;
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}
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.table thead th {
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background-color: rgba(30, 41, 59, 0.5);
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border-bottom: 1px solid rgba(56, 189, 248, 0.3);
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color: #67e8f9;
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}
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.table tbody tr {
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border-bottom: 1px solid rgba(56, 189, 248, 0.1);
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}
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.table tbody tr:hover {
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background-color: rgba(30, 41, 59, 0.3);
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}
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.collapse-title {
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background: rgba(30, 41, 59, 0.3);
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}
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.collapse:focus-within .collapse-title {
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background: rgba(30, 41, 59, 0.5);
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}
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.background-aura {
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position: fixed;
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top: 0;
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left: 0;
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width: 100%;
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height: 100%;
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z-index: -10;
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overflow: hidden;
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background-color: #010008;
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}
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.aura-light {
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position: absolute;
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border-radius: 50%;
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filter: blur(150px);
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opacity: 0.15;
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}
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</style>
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</head>
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<body class="min-h-screen">
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<div class="background-aura">
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<div class="aura-light" style="width: 800px; height: 800px; background: #38bdf8; top: -20%; left: -15%;"></div>
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<div class="aura-light" style="width: 700px; height: 700px; background: #c084fc; bottom: -25%; right: -10%;"></div>
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</div>
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<div class="container mx-auto p-4 md:p-8 max-w-7xl">
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<header class="text-center mb-12">
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<h1 class="text-4xl md:text-6xl font-bold title-gradient glow-text">AI算力芯片 深度研究报告</h1>
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<p class="mt-4 text-slate-400">北京价值前沿科技有限公司 AI投研agent：“价小前投研”</p>
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<p class="text-sm text-slate-500 mt-1">本报告为AI合成数据，投资需谨慎。</p>
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</header>
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<main x-data="{ tab: 'insight' }">
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<!-- INSIGHT Section -->
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<section id="insight" class="mb-12">
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<div class="bento-grid">
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<!-- Core View -->
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<div class="col-span-12 bento-item glass-card">
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<h2 class="text-2xl font-bold mb-4 glow-text-cyan">核心观点摘要</h2>
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<p class="text-slate-300 leading-relaxed">
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AI算力芯片正处于由<strong class="text-sky-300">全球需求爆发</strong>和<strong class="text-fuchsia-300">国内供给重构</strong>双轮驱动的黄金发展期。其核心逻辑在于，一方面英伟达通过持续的技术迭代 (Blackwell, Rubin) 和强大的CUDA生态定义了全球AI算力的技术范式与天花板；另一方面，地缘政治因素催生了以华为昇腾为核心的、政策与市场双重加持的国产算力体系，形成了独特的<strong class="text-sky-300">“一个世界，两个体系”</strong>格局。当前阶段，市场的焦点在于验证国产芯片在真实商业场景下的性能、成本与生态成熟度。
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</p>
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</div>
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<!-- Market Drivers -->
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<div class="col-span-12 lg:col-span-8 col-span-md-12 bento-item glass-card">
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<h3 class="text-xl font-semibold mb-3 glow-text-cyan">核心驱动力</h3>
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<ul class="space-y-3 text-slate-300">
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<li><strong>需求侧 - AI大模型军备竞赛：</strong>大模型技术持续演进，算力需求呈指数级增长。全球云厂商资本开支持续上修是需求最直接的体现。</li>
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<li><strong>供给侧 - 地缘政治下的“强制替代”：</strong>美国出口管制是决定性的外生变量，为国产芯片提供了前所未有的市场准入和试错机会。运营商近<strong class="text-amber-400">300亿</strong>规模的集采以国产芯片为主，是这一逻辑的铁证。</li>
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<li><strong>经济性驱动 - 成本与效率博弈：</strong>全球范围内，云厂商自研ASIC芯片的核心动机是降本增效。谷歌TPU的单位算力成本仅为英伟达H100的<strong class="text-green-400">70%</strong>，驱动GPU与ASIC两种技术路线并行发展。</li>
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</ul>
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</div>
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<!-- Chart -->
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<div class="col-span-12 lg:col-span-4 col-span-md-12 bento-item glass-card flex flex-col items-center justify-center">
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<h3 class="text-xl font-semibold mb-3 glow-text-cyan">全球GPU市场格局 (2023)</h3>
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<div id="marketShareChart" style="width: 100%; height: 250px;"></div>
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</div>
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<!-- Catalysts -->
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<div class="col-span-12 lg:col-span-6 col-span-md-12 bento-item glass-card">
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<h3 class="text-xl font-semibold mb-3 glow-text-fuchsia">关键催化剂</h3>
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<ul class="space-y-3 text-slate-300">
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<li><strong class="text-fuchsia-300">近期 (3-6个月)：</strong>华为昇腾910C规模商用反馈、英伟达Blackwell财报贡献、国产AI芯片公司IPO进展、地方智算中心补贴等政策落地。</li>
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<li><strong class="text-fuchsia-300">长期发展路径：</strong>
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<ul class="list-disc list-inside ml-2 mt-1 text-sm text-slate-400">
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<li><strong>追赶期 (当前-2026)：</strong>国产芯片卡位政策市场，向商业市场渗透，完善软件生态。</li>
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<li><strong>并存期 (2026-2028)：</strong>在推理端和特定训练场景实现大规模应用，形成差异化竞争。</li>
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<li><strong>融合/对抗期 (2028+)：</strong>若先进制程突破，有望形成两大生态体系对抗。</li>
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</ul>
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</li>
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</ul>
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</div>
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<!-- Risks -->
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<div class="col-span-12 lg:col-span-6 col-span-md-12 bento-item glass-card">
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<h3 class="text-xl font-semibold mb-3 glow-text text-red-400">潜在风险与挑战</h3>
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<ul class="space-y-3 text-slate-300">
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<li><strong class="text-red-400">技术风险：</strong>CUDA生态壁垒难以逾越；国内先进制程与台积电差距显著，限制性能上限；集群互联效率（NVLink vs 国产方案）差距导致有效算力折扣。</li>
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<li><strong class="text-red-400">商业化风险：</strong>国产芯片的综合TCO（总拥有成本）在商业市场可能不具备优势。英伟达单卡性价比高<strong class="text-amber-400">20%-50%</strong>，降价压力不大。</li>
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<li><strong class="text-red-400">信息交叉验证风险：</strong>市场普遍乐观情绪（新闻、研报）与产业实际差距（路演纪要）存在偏差，即“外热内冷”。</li>
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</ul>
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</div>
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</div>
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</section>
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<!-- Industry Chain Section -->
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<section class="mb-12 glass-card rounded-3xl p-6">
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<h2 class="text-2xl font-bold mb-4 glow-text-cyan">产业链深度剖析与投资启示</h2>
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<div class="grid grid-cols-1 lg:grid-cols-2 gap-8">
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<div>
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<h3 class="text-xl font-semibold mb-3 glow-text-fuchsia">产业链图谱</h3>
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<ul class="space-y-2 text-slate-300 text-sm">
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<li><strong>上游 (基础支撑):</strong>
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<span class="text-slate-400">芯片设计 (景嘉微, 寒武纪), 制造与封装 (中芯国际), 核心材料/组件 (沪电股份, 杰华特)</span>
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</li>
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<li><strong>中游 (算力提供):</strong>
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<span class="text-slate-400">芯片厂商 (英伟达, AMD; <strong class="text-amber-400">华为</strong>, 寒武纪, 海光信息)</span>
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</li>
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<li><strong>下游 (算力应用):</strong>
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<span class="text-slate-400">服务器/一体机 (中兴通讯, 紫光股份), 云服务/数据中心, AI应用</span>
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</li>
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</ul>
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<h3 class="text-xl font-semibold mt-6 mb-3 glow-text-fuchsia">核心玩家对比</h3>
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<div class="space-y-4 text-sm">
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<p><strong><span class="text-sky-300">英伟达:</span></strong> 绝对技术和生态霸主，优势在于性能、CUDA生态和供应链掌控力。</p>
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<p><strong><span class="text-amber-400">华为昇腾:</span></strong> 逻辑最纯粹的国产替代龙头，优势在于全栈自研、政策支持和商业化落地能力。</p>
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<p><strong><span class="text-purple-300">寒武纪 & 海光信息:</span></strong> 国内追赶者。寒武纪布局云边端一体，海光信息具备"CPU+DCU"协同及兼容"类CUDA"生态优势，但在华为挤压下面临竞争压力。</p>
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</div>
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</div>
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<div>
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<h3 class="text-xl font-semibold mb-3 glow-text-green-400">综合结论与投资启示</h3>
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<p class="mb-4 text-slate-300">AI算力芯片概念正处在<strong class="text-green-300">基本面驱动</strong>与<strong class="text-fuchsia-300">主题催化</strong>共振的加速阶段。</p>
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<h4 class="font-semibold text-green-300 mb-2">最具投资价值的细分环节：</h4>
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<ol class="list-decimal list-inside space-y-2 text-slate-300">
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<li><strong>国产算力核心设备商的供应链：</strong>特别是华为昇腾链条中技术壁垒高、价值量大的部分（高性能PCB、ABF载板、AI服务器电源模块），业绩确定性最强。</li>
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<li><strong>先进封装与测试：</strong>作为产业链共同瓶颈，具备长期成长逻辑。</li>
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<li><strong>光互联：</strong>随着集群规模扩大，高速光模块/光芯片需求将持续爆发，是产业链中弹性最高的环节之一。</li>
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</ol>
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<h4 class="font-semibold text-green-300 mt-6 mb-2">需重点跟踪的关键指标：</h4>
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<ul class="list-disc list-inside space-y-1 text-sm text-slate-400">
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<li>国产芯片出货量与商业客户占比。</li>
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<li>国产大模型与国产芯片的适配深度与效率。</li>
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<li>台积电CoWoS产能扩张进度。</li>
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<li>国内先进制程（如中芯国际）突破进展。</li>
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||||
</ul>
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||||
</div>
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||||
</div>
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||||
</section>
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||||
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<!-- Supporting Data Tabs -->
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<section class="mb-12">
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<div role="tablist" class="tabs tabs-lifted">
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||||
<button role="tab" class="tab" :class="{'tab-active': tab === 'data'}" @click="tab = 'data'">原始情报数据</button>
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||||
<button role="tab" class="tab" :class="{'tab-active': tab === 'rise'}" @click="tab = 'rise'">涨幅归因分析</button>
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</div>
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||||
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||||
<div class="glass-card rounded-b-2xl rounded-tr-2xl p-6" x-show="tab === 'data'" x-data="{ subTab: 'news' }">
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||||
<div role="tablist" class="tabs tabs-boxed bg-slate-900/50 mb-4">
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||||
<a role="tab" class="tab" :class="{'tab-active': subTab === 'news'}" @click="subTab = 'news'">新闻数据</a>
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||||
<a role="tab" class="tab" :class="{'tab-active': subTab === 'roadshow'}" @click="subTab = 'roadshow'">路演纪要</a>
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<a role="tab" class="tab" :class="{'tab-active': subTab === 'report'}" @click="subTab = 'report'">研究报告</a>
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||||
</div>
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||||
|
||||
<!-- News Data -->
|
||||
<div x-show="subTab === 'news'" class="space-y-4 max-h-[600px] overflow-y-auto pr-2">
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||||
<div class="collapse collapse-arrow glass-card">
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<input type="radio" name="news-accordion" checked="checked" />
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||||
<div class="collapse-title text-xl font-medium glow-text-cyan">全球市场与头部厂商动态</div>
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||||
<div class="collapse-content text-slate-300 text-sm space-y-2">
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<p><strong>英伟达(Nvidia):</strong> 新产品DGXB200交付顺利；财报展望乐观，推出Spectrum-XGS以太网；Blackwell方案采用台积电CoWoS封装；单卡性价比高20%-50%，降价压力不大；亚马逊拿下OpenAI 380亿算力订单，将供应英伟达芯片。</p>
|
||||
<p><strong>博通(Broadcom):</strong> 全球AI加速芯片两大龙头之一，季报超预期。</p>
|
||||
<p><strong>谷歌(Google):</strong> “捕光者”计划27年将发射Trillium TPU验证分布式训练。</p>
|
||||
<p><strong>Credo:</strong> 受益于亚马逊、微软等AI芯片用量，营收将放量。</p>
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||||
</div>
|
||||
</div>
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="news-accordion" />
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||||
<div class="collapse-title text-xl font-medium glow-text-fuchsia">国产AI芯片发展与市场格局</div>
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||||
<div class="collapse-content text-slate-300 text-sm space-y-2">
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||||
<p><strong>总体趋势:</strong> 国产大模型与芯片适配盘活存量资产，国产算力替代空间正在打开，产业迈向整体崛起。</p>
|
||||
<p><strong>华为昇腾:</strong> 政府市场份额达80-85%；910C算力接近H100的80-90%，预计明年出货40-60万；软件生态国内最强。</p>
|
||||
<p><strong>寒武纪:</strong> 与昇腾一同进入批量商业化出货；产品在特定算法上优于A100；PyTorch代码迁移便捷。</p>
|
||||
<p><strong>海光信息:</strong> 深算3号性能强于A100，有望实现千卡集群。</p>
|
||||
<p><strong>中兴通讯:</strong> 具备GPU/CPU/DPU全栈设计能力，51.2T交换芯片领先。</p>
|
||||
<p><strong>阿里平头哥:</strong> 自研芯片测试方案与利扬芯片合作，但受限于先进制程供给尚未放量。</p>
|
||||
<p><strong>摩尔线程 & 沐曦:</strong> 已提交IPO申请，专注高性能GPU研发。</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="news-accordion" />
|
||||
<div class="collapse-title text-xl font-medium glow-text-cyan">未来趋势与市场分析</div>
|
||||
<div class="collapse-content text-slate-300 text-sm space-y-2">
|
||||
<p><strong>系统级算力:</strong> 单芯片算力提升放缓，系统级节点有望成为AI算力发展的重要方向，为国产GPU提供追赶机遇。</p>
|
||||
<p><strong>太空算力:</strong> 概念兴起，旨在解决AI缺电问题，已有公司发射NVIDIA H100上太空。</p>
|
||||
<p><strong>集群互联:</strong> 单颗芯片性能接近物理极限，通信互联决定集群能力上限。</p>
|
||||
<p><strong>需求周期:</strong> 市场普遍认为25H1推理需求先起，25H2训练需求再起。</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<!-- Roadshow Data -->
|
||||
<div x-show="subTab === 'roadshow'" class="space-y-4 max-h-[600px] overflow-y-auto pr-2">
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="roadshow-accordion" checked/>
|
||||
<div class="collapse-title text-xl font-medium glow-text-cyan">国产替代与市场格局</div>
|
||||
<div class="collapse-content text-slate-300 text-sm space-y-2">
|
||||
<p><strong>制裁影响:</strong> 美国对A800/H800的限制为华为、寒武纪、海光提供了替代机会。英伟达H20等降级版难以满足大模型训练需求。</p>
|
||||
<p><strong>华为昇腾主导:</strong> 占据国内AI服务器芯片约40%份额，训练卡领先。910B对标A100，预计24年底发布的910C对标H系列。24年出货量或翻倍，但受产能限制。</p>
|
||||
<p><strong>海光&寒武纪追赶:</strong> 主要聚焦推理或小模型训练，与华为存在算力差距。海光24年下半年新品算力预计与昇腾910B相当。</p>
|
||||
<p><strong>技术差距:</strong> 国产芯片在生态系统、数据交换带宽、代工能力上与英伟达差距显著。华为昇腾是唯一完全自研架构，但生态尚未成熟。</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="roadshow-accordion" />
|
||||
<div class="collapse-title text-xl font-medium glow-text-fuchsia">大厂自研与技术路线</div>
|
||||
<div class="collapse-content text-slate-300 text-sm space-y-2">
|
||||
<p><strong>自研驱动力:</strong> 降本增效（谷歌TPU v5p能效比优于NVIDIA）和供应链安全是核心驱动。</p>
|
||||
<p><strong>全球格局:</strong> 谷歌(TPU)、微软(Maia100)、亚马逊(Trainium)、Meta(MTIA)均推出自研芯片，但性能仍落后于H100。</p>
|
||||
<p><strong>国内格局:</strong> 百度昆仑芯、阿里含光系列已量产，但高端训练芯片仍依赖英伟达。共性问题是先进制程受限和生态建设滞后。</p>
|
||||
<p><strong>ASIC vs GPGPU:</strong> ASIC在算力密度和能效上具优势，GPGPU在显存带宽和互联技术上领先。推理端需求增长（占英伟达数据中心收入40%）利好ASIC发展。</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="roadshow-accordion" />
|
||||
<div class="collapse-title text-xl font-medium glow-text-cyan">供应链与产能</div>
|
||||
<div class="collapse-content text-slate-300 text-sm space-y-2">
|
||||
<p><strong>产能瓶颈:</strong> 台积电CoWoS 2.5D封装是英伟达GPU产能关键，2025年目标月产9万片。CoWoS产能结构性紧缺，优先保障英伟达、AMD。</p>
|
||||
<p><strong>华为昇腾产业链:</strong> 是国产算力卡中唯一具备充足产能的。昇腾芯片功耗激增驱动供电模块价值量提升（杰华特是唯一供应商），PCB层数升级（利好新生科技等）。中芯国际是其核心代工厂。</p>
|
||||
<p><strong>HBM内存:</strong> SK海力士已量产12层HBM3E，是AI芯片关键组件。</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<!-- Report Data -->
|
||||
<div x-show="subTab === 'report'" class="space-y-4 max-h-[600px] overflow-y-auto pr-2">
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="report-accordion" checked/>
|
||||
<div class="collapse-title text-xl font-medium glow-text-cyan">市场现状与格局</div>
|
||||
<div class="collapse-content text-slate-300 text-sm space-y-2">
|
||||
<p><strong>核心地位:</strong> AI算力芯片是"AI时代的引擎"，占AI服务器成本主要部分（GPU占比可达72.8%）。</p>
|
||||
<p><strong>英伟达主导:</strong> 2023年英伟达在数据中心GPU出货量中占据98%的市场份额，CUDA生态建立强大壁垒。</p>
|
||||
<p><strong>ASIC高速成长:</strong> 云厂商自研趋势明显，推动定制ASIC市场高速成长，预计2023-2028年复合增速达45%。博通是全球AI ASIC龙头。</p>
|
||||
<p><strong>市场规模:</strong> 预计全球GPU市场规模将从2023年的436亿美元增长至2029年的2742亿美元。</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="report-accordion"/>
|
||||
<div class="collapse-title text-xl font-medium glow-text-fuchsia">技术类型与对比</div>
|
||||
<div class="collapse-content text-slate-300 text-sm space-y-2">
|
||||
<p><strong>GPU vs ASIC:</strong> GPU更适用于需要高并行计算能力的训练场景；ASIC能效比最高，单位算力成本更低，更适用于大规模、固定的推理场景。</p>
|
||||
<p><strong>单位成本对比:</strong> 谷歌TPU v5单位算力成本为H100的70%，亚马逊Trainium 2为H100的60%。</p>
|
||||
<p><strong>核心评测指标:</strong> TOPS (算力)、TOPS/W (能效比)、内存带宽、算力利用率。</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="report-accordion"/>
|
||||
<div class="collapse-title text-xl font-medium glow-text-cyan">驱动因素与支撑技术</div>
|
||||
<div class="collapse-content text-slate-300 text-sm space-y-2">
|
||||
<p><strong>核心驱动:</strong> 大模型发展引爆算力需求；地缘政治催生国产替代黄金期；推理需求加速释放提供广阔空间。</p>
|
||||
<p><strong>DeepSeek模型推动:</strong> 通过MoE架构、FP8等技术实现极高性价比，并已全面适配华为昇腾等20余家国产芯片，推动国产软硬件生态闭环。</p>
|
||||
<p><strong>支撑技术:</strong> HBM (高带宽存储器) 解决内存瓶颈；先进封装 (CoWoS) 是集成HBM与GPU的主流方案；未来技术包括Chiplet、存算一体等。</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="glass-card rounded-b-2xl rounded-tr-2xl p-6" x-show="tab === 'rise'" >
|
||||
<div class="space-y-4 max-h-[600px] overflow-y-auto pr-2">
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="rise-accordion" checked="checked" />
|
||||
<div class="collapse-title text-lg font-medium">利扬芯片 (688135) <span class="text-success ml-2">+20.0%</span></div>
|
||||
<div class="collapse-content text-slate-300 text-sm">
|
||||
<p><strong>核心结论:</strong> 阿里宣布三年3000亿元AI投资计划，利扬芯片作为其AI芯片测试核心供应商，订单弹性被资金瞬间重估，20cm涨停。<br><strong>驱动概念:</strong> 阿里AI投资计划+国产算力芯片测试环节+3nm先进制程测试能力</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="rise-accordion" />
|
||||
<div class="collapse-title text-lg font-medium">华正新材 (603186) <span class="text-success ml-2">+10.0%</span></div>
|
||||
<div class="collapse-content text-slate-300 text-sm">
|
||||
<p><strong>核心结论:</strong> 美国新一轮AI芯片出口管制将华为昇腾推上风口，公司被官方认证为昇腾910C封装基板CCL第一供应商，2026年利润弹性翻倍，机构抢筹导致涨停。<br><strong>驱动概念:</strong> 昇腾国产算力+AI芯片替代+先进封装</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="rise-accordion" />
|
||||
<div class="collapse-title text-lg font-medium">拓维信息 (002261) <span class="text-success ml-2">+10.0%</span></div>
|
||||
<div class="collapse-content text-slate-300 text-sm">
|
||||
<p><strong>核心结论:</strong> 半年报业绩暴增22倍正式落地，叠加昇腾AI算力订单集中确认与政策共振，资金集中回补。<br><strong>驱动概念:</strong> 昇腾AI算力+东数西算二期+国产芯片</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="rise-accordion" />
|
||||
<div class="collapse-title text-lg font-medium">川润股份 (002272) <span class="text-success ml-2">+9.98%</span></div>
|
||||
<div class="collapse-content text-slate-300 text-sm">
|
||||
<p><strong>核心结论:</strong> 网信办通报英伟达H20芯片安全隐患，国产算力替代预期升温，川润股份作为昇腾AI服务器液冷核心配套商被资金抢筹。<br><strong>驱动概念:</strong> 国产算力替代+液冷服务器+昇腾AI</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="collapse collapse-arrow glass-card">
|
||||
<input type="radio" name="rise-accordion" />
|
||||
<div class="collapse-title text-lg font-medium">中芯国际 (688981) <span class="text-success ml-2">+14.19%</span></div>
|
||||
<div class="collapse-content text-slate-300 text-sm">
|
||||
<p><strong>核心结论:</strong> AI算力需求爆发与国产替代加速，中芯国际作为国内芯片制造环节的核心战略地位凸显，叠加板块联动与主力资金大规模流入，引发股价大涨。<br><strong>驱动概念:</strong> 芯片国产替代+AI算力需求+晶圆代工</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
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|
||||
|
||||
<!-- Stock List Section -->
|
||||
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|
||||
<h2 class="text-2xl font-bold mb-6 text-center glow-text-cyan">相关概念股一览</h2>
|
||||
<div class="overflow-x-auto">
|
||||
<table class="table table-zebra w-full">
|
||||
<thead>
|
||||
<tr>
|
||||
<th>股票名称</th>
|
||||
<th>股票代码</th>
|
||||
<th>核心逻辑</th>
|
||||
<th>技术标签</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<!-- GPU -->
|
||||
<tr>
|
||||
<td class="font-semibold text-sky-300">景嘉微</td>
|
||||
<td><a href="https://valuefrontier.cn/company?scode=300474" target="_blank" class="link link-hover">300474</a></td>
|
||||
<td>国产GPU龙头</td>
|
||||
<td><span class="badge badge-info badge-outline">GPU</span></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td class="font-semibold text-sky-300">寒武纪</td>
|
||||
<td><a href="https://valuefrontier.cn/company?scode=688256" target="_blank" class="link link-hover">688256</a></td>
|
||||
<td>领先AI芯片设计公司，思元系列芯片</td>
|
||||
<td><span class="badge badge-info badge-outline">GPU</span> <span class="badge badge-accent badge-outline">ASIC</span></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td class="font-semibold text-sky-300">海光信息</td>
|
||||
<td><a href="https://valuefrontier.cn/company?scode=688041" target="_blank" class="link link-hover">688041</a></td>
|
||||
<td>国产CPU+GPU龙头</td>
|
||||
<td><span class="badge badge-info badge-outline">GPU</span></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td class="font-semibold text-sky-300">龙芯中科</td>
|
||||
<td><a href="https://valuefrontier.cn/company?scode=688047" target="_blank" class="link link-hover">688047</a></td>
|
||||
<td>自主研发GPU</td>
|
||||
<td><span class="badge badge-info badge-outline">GPU</span></td>
|
||||
</tr>
|
||||
<!-- FPGA -->
|
||||
<tr>
|
||||
<td class="font-semibold text-purple-300">紫光国微</td>
|
||||
<td><a href="https://valuefrontier.cn/company?scode=002049" target="_blank" class="link link-hover">002049</a></td>
|
||||
<td>已突破FPGA高制程技术</td>
|
||||
<td><span class="badge badge-secondary badge-outline">FPGA</span></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td class="font-semibold text-purple-300">复旦微电</td>
|
||||
<td><a href="https://valuefrontier.cn/company?scode=688385" target="_blank" class="link link-hover">688385</a></td>
|
||||
<td>国产FPGA头部厂商</td>
|
||||
<td><span class="badge badge-secondary badge-outline">FPGA</span></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td class="font-semibold text-purple-300">安路科技</td>
|
||||
<td><a href="https://valuefrontier.cn/company?scode=688107" target="_blank" class="link link-hover">688107</a></td>
|
||||
<td>国内民用FPGA</td>
|
||||
<td><span class="badge badge-secondary badge-outline">FPGA</span></td>
|
||||
</tr>
|
||||
<!-- ASIC -->
|
||||
<tr>
|
||||
<td class="font-semibold text-fuchsia-300">澜起科技</td>
|
||||
<td><a href="https://valuefrontier.cn/company?scode=688008" target="_blank" class="link link-hover">688008</a></td>
|
||||
<td>计算类芯片集成</td>
|
||||
<td><span class="badge badge-accent badge-outline">ASIC</span></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td class="font-semibold text-fuchsia-300">紫光股份</td>
|
||||
<td><a href="https://valuefrontier.cn/company?scode=000938" target="_blank" class="link link-hover">000938</a></td>
|
||||
<td>自研芯片，服务器龙头</td>
|
||||
<td><span class="badge badge-accent badge-outline">ASIC</span></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td class="font-semibold text-fuchsia-300">华为海思</td>
|
||||
<td><span class="text-slate-500">未上市</span></td>
|
||||
<td>自研昇腾系列芯片，国产算力核心</td>
|
||||
<td><span class="badge badge-accent badge-outline">ASIC</span></td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
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|
||||
</section>
|
||||
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||||
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|
||||
itemStyle: { color: new echarts.graphic.LinearGradient(0, 0, 0, 1, [{offset: 0, color: '#4b5563'}, {offset: 1, color: '#1f2937'}]) }
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
};
|
||||
myChart.setOption(option);
|
||||
window.addEventListener('resize', myChart.resize);
|
||||
});
|
||||
</script>
|
||||
|
||||
</body>
|
||||
</html>
|
||||
Reference in New Issue
Block a user