[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"site-home-live-entry-setting":3,"site-header-contests":8,"site-header-camps":49,"study-material-detail-study-71":104},{"enabled":4,"title":5,"statusText":5,"buttonText":5,"campSlug":5,"stage":6,"classroomId":7,"hasClassroom":4},false,"",0,null,{"total":9,"list":10,"pageNum":44,"pageSize":45,"size":9,"startRow":44,"endRow":9,"pages":44,"prePage":6,"nextPage":6,"isFirstPage":46,"isLastPage":46,"hasPreviousPage":4,"hasNextPage":4,"navigatePages":47,"navigatepageNums":48,"navigateFirstPage":44,"navigateLastPage":44},3,[11,25,35],{"slug":12,"title":13,"logo":7,"liveUrl":14,"prize":15,"sponsor":16,"description":17,"organizer":18,"startTime":19,"endTime":20,"registrationDeadline":21,"status":22,"dashboardVisibility":23,"createdAt":24},"spring2026","2026春季启元人工智能大赛","https:\u002F\u002Fwww.bilibili.com\u002Fblackboard\u002Flive\u002Flive-activity-player.html?cid=1822703816&quality=0","200,000","麒麟软件有限公司","“2026春季启元人工智能大赛”是由启元实验室主办的面向全国人工智能领域开发者、科研人员及高校学生的权威赛事。大赛旨在促进与培养具备工程实践能力和创新能力的优秀人工智能领域开发者、推广国产软硬件技术与生态、助力国家人工智能产业高质量发展。\n各参赛选手需在规定的比赛周期内，依据赛事规则选定赛题并完成相应挑战，优胜者将共同角逐总额20万元的赛事奖金池，并且还将有机会获得实习和知名企业优质岗位内推资格。","启元实验室","2026-04-19 16:00:00","2026-07-13 16:00:00","2026-06-16 16:00:00","ongoing","private","2026-04-16 08:00:00",{"slug":26,"title":27,"logo":7,"liveUrl":14,"prize":28,"sponsor":7,"description":29,"organizer":18,"startTime":30,"endTime":31,"registrationDeadline":32,"status":33,"dashboardVisibility":23,"createdAt":34},"autumn2025","2025秋季启元人工智能大赛","150,000","“2025秋季启元人工智能大赛”是由启元实验室主办的面向全国人工智能领域开发者、科研人员及高校学生的权威赛事。大赛旨在促进与培养具备工程实践能力和创新能力的优秀人工智能领域开发者、推广国产软硬件技术与生态、助力国家人工智能产业高质量发展。","2025-11-08 08:00:00","2026-01-13 08:00:00","2025-12-30 08:00:00","ended","2025-11-03 08:00:00",{"slug":36,"title":37,"logo":7,"liveUrl":14,"prize":38,"sponsor":7,"description":39,"organizer":18,"startTime":40,"endTime":41,"registrationDeadline":42,"status":33,"dashboardVisibility":23,"createdAt":43},"summer2025","启元人工智能大赛(系统方向)","80,000","启元人工智能大赛由启元实验室主办，其中系统赛道基于启元实验室九源软件栈的相关开源项目，通过拉动开源社区力量，一方面促进国产智能计算生态的发展，另一方面也为人工智能系统方向的学生及从业者提供一个实践平台。","2025-07-08 08:00:00","2025-08-25 08:00:00","2025-07-22 08:00:00","2025-06-22 08:00:00",1,5,true,8,[44],{"total":45,"list":50,"pageNum":44,"pageSize":45,"size":45,"startRow":44,"endRow":45,"pages":44,"prePage":6,"nextPage":6,"isFirstPage":46,"isLastPage":46,"hasPreviousPage":4,"hasNextPage":4,"navigatePages":47,"navigatepageNums":103,"navigateFirstPage":44,"navigateLastPage":44},[51,62,73,84,94],{"id":52,"slug":53,"title":54,"logo":55,"publicLiveEmbedUrl":14,"description":56,"introduction":57,"organizer":18,"coOrganizer":5,"sponsor":16,"startTime":58,"endTime":59,"status":22,"dashboardVisibility":60,"createdAt":58,"updatedAt":61},"019eeeff-6b00-7d55-a629-efafded3e232","summer2026","2026年夏季InfiniTensor大模型与人工智能系统训练营","https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fuploads\u002F2026-06\u002F019eef7f-7816-7828-9309-79c2c61dd568.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=fLKIdTmv5ztTF5lNyW4vFO%2FwiU4%3D","由启元实验室发起的InfiniTensor大模型与人工智能系统训练营，面向开源社区、高校及产业界伙伴开放。活动以「普及AI全栈知识技术、培养工程实践与创新型人才、推广国产软硬件技术生态」为核心目标，助力国家人工智能产业高质量发展。","...","2026-06-22 08:00:00","2026-10-19 08:00:00","public","2026-10-12 08:00:00",{"id":63,"slug":64,"title":65,"logo":66,"publicLiveEmbedUrl":7,"description":67,"introduction":57,"organizer":18,"coOrganizer":5,"sponsor":68,"startTime":69,"endTime":70,"status":33,"dashboardVisibility":23,"createdAt":71,"updatedAt":72},"019af3f3-e06a-7245-aa8d-37dc99a69c73","winter2025","2025年冬季InfiniTensor大模型与人工智能系统训练营","https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fuploads\u002F2025-12\u002F019afc69-b7ca-7805-91fb-605429671c01.png?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=IfcKyBkOe6Ug2cb8ODO9I1IUNkA%3D","由启元实验室发起的InfiniTensor大模型与人工智能系统训练营，面向开源社区、高校及产业界伙伴开放。活动以「普及AI全栈知识技术、培养工程实践与创新型人才、推广国产软硬件技术生态」为核心目标，助力国家人工智能产业高质量发展。 \n","新华三技术有限公司","2025-12-25 08:00:00","2026-03-27 08:00:00","2025-12-06 08:00:00","2026-10-22 20:24:30",{"id":74,"slug":36,"title":75,"logo":76,"publicLiveEmbedUrl":7,"description":77,"introduction":57,"organizer":18,"coOrganizer":5,"sponsor":78,"startTime":79,"endTime":80,"status":81,"dashboardVisibility":23,"createdAt":82,"updatedAt":83},"01980342-208c-7803-b3f3-19e1d31960ba","2025年夏季InfiniTensor大模型与人工智能系统训练营","https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fuploads\u002F2025-07\u002F0198045e-28fe-78f0-95fe-23835ce58395.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=Ev4DWdZSXJ0t1T4u2JL5qybAazs%3D","InfiniTensor大模型与人工智能系统训练营由启元实验室及清华大学 AI 系统方向团队发起，面向开源社区、高校和产业界，普及人工智能各方面知识和技术，培养相关人才。训练营联合开源项目开发者、学术界大牛、工业界资深工程师参与授课与项目指导。课程采用「线上直播授课 + 在线答疑 + 项目实践辅导 」的方式进行，确保每位同学都能获得充分成长。训练营全程免费，通过视频、直播课、习题和项目实践，在人工智能飞速发展的背景下，为学员提供一窥深层技术的机会。","北京积算科技有限公司","2025-07-14 08:00:00","2025-09-30 08:00:00","upcoming","2025-07-13 08:00:00","2026-10-22 20:24:58",{"id":85,"slug":86,"title":87,"logo":88,"publicLiveEmbedUrl":7,"description":89,"introduction":57,"organizer":18,"coOrganizer":5,"sponsor":5,"startTime":90,"endTime":91,"status":81,"dashboardVisibility":23,"createdAt":92,"updatedAt":93},"01980cf9-a7d8-7796-ae86-0bbe05334add","winter2024","2024年冬季InfiniTensor大模型与人工智能系统训练营","https:\u002F\u002Ftesting-cdn.infinitensor.com\u002Fuploads\u002F2025-07\u002F01981269-ce23-7624-a287-9f07dd0d85f6.jpg","InfiniTensor大模型与人工智能系统训练营由清华大学发起，面向开源社区、高校和产业界，普及人工智能各方面知识和技术，培养相关人才。训练营全程免费，通过视频、直播课、习题和项目实践，在人工智能飞速发展的背景下，为学员提供一窥深层技术的机会。报名学员请阅读“导学”课程页的训练营介绍。","2025-01-05 08:00:00","2025-03-22 08:00:00","2025-07-15 08:00:00","2026-10-22 20:24:39",{"id":95,"slug":96,"title":97,"logo":98,"publicLiveEmbedUrl":7,"description":99,"introduction":57,"organizer":18,"coOrganizer":5,"sponsor":5,"startTime":100,"endTime":101,"status":81,"dashboardVisibility":23,"createdAt":92,"updatedAt":102},"01980c20-363a-7dc3-8f5a-58a68e08dcc4","summer2024","2024年夏季InfiniTensor大模型与人工智能系统训练营","https:\u002F\u002Ftesting-cdn.infinitensor.com\u002Fuploads\u002F2025-07\u002F01981269-fbfa-788a-afcd-17fa9be74ff9.jpg","InfiniTensor大模型与人工智能系统训练营由清华大学发起，面向开源社区和高校，普及人工智能各方面知识和技术，培养相关人才。训练营全程免费，通过课程、习题和项目实践，在人工智能飞速发展的背景下，为学员提供一窥深层技术的机会。","2024-07-20 08:00:00","2024-09-29 08:00:00","2026-10-22 20:24:49",[44],{"currentItem":105,"processedData":125},{"img":106,"keywords":107,"treeType":44,"description":108,"showStatus":44,"updateTime":109,"type":110,"title":111,"content":112,"nextArticle":113,"createTime":109,"sortOrder":117,"canonicalPath":118,"id":119,"contentType":120,"prevArticle":121},"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_fm.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=KvvnKY%2Fq3hXZwGsxUwOSSMKIB8Q%3D","OpenCL,异构并行,跨平台编程,Kernel,运行时 API","介绍跨平台并行标准 OpenCL，拆解平台、设备、上下文、Kernel 等 12 步运行时 API 全流程，对比 CUDA，讲解端侧异构设备适配优势。","2026-10-22 20:38:11",2,"2026 夏季 InfiniTensor 训练营 OpenCL 编程 1：《OpenCL 概述与运行时》","![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw01.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=rgfq5bAXaJ1HY7cMxuoxCoyD%2Fx0%3D)\r\n\r\n\r\n\u003Cspan style=\"font-size:12px;color:#555;\">7 月 21 日，2026 夏季 InfiniTensor 训练营 OpenCL 编程方向第一课《OpenCL 概述与运行时》开讲。\r\n\u003C\u002Fspan>\r\n\r\n本节课作为 OpenCL 系列课程的开篇，将帮大家建立对 OpenCL 的正确认知。从“为什么要学”出发，通过生动的类比，拆解 OpenCL 看似复杂的运行时流程，为后续的实战课程打下坚实基础。\r\n\r\n\r\n\r\n## 认识 OpenCL\r\n### 什么是 OpenCL？\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw02.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=h0ngMWXHc62SNH1I%2BXt5g7cRRLQ%3D)\r\n\r\n1. 全称：Open Computing Language\r\n2. 本质：为异构平台提供统一并行编程框架的开放标准\r\n3. 核心能力：通过统一 API 支持 CPU、GPU、FPGA、NPU 等混合设备并行计算\r\n\r\n### 为什么要学 OpenCL 而不是直接学 CUDA？\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw03.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=so%2F44weBJUhJN27fDpu2DH6ar98%3D)\r\n\r\n1. **跨平台优势**：一套代码适配多厂商硬件（NVIDIA\u002FAMD\u002FIntel\u002F高通等），牺牲极致性能换取通用性与可移植性\r\n2. **低门槛与低成本**：不依赖昂贵的高端显卡，低端设备甚至 CPU（支持超线程\u002FOpenCL 驱动）即可开发验证\r\n3. **关注并行本质**：相比 CUDA 的设备绑定，OpenCL 更侧重于并行计算思维本身的训练\r\n\r\n### 端侧部署的现实需求\r\n1. **云侧痛点**：集群建设成本高、网络延迟、隐私泄露风险\r\n2. **端侧优势**：隐私性强、成本可控、Token 消耗无压力（Agent 应用友好）\r\n3. **算力现状**：端侧加速卡碎片化严重，OpenCL 是解决“多设备适配”的最优解之一\r\n\r\n## OpenCL 程序\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw04.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=h8zpQZiq8c3ZTywf2YjioS%2BrpoY%3D)\r\n\r\n#### 1. Platform（平台）：\r\n- OpenCL 实现提供者提供的软件抽象层，用于管理一组 OpenCL 设备，通常由硬件厂商驱动或第三方 OpenCL 实现提供，例如 NVIDIA、Intel 等\r\n- **获取平台信息 (`clGetPlatformIDs`)**\r\n  - 类比：确定宴席举办地点\r\n  - 要点：C 语言风格 API，需检查返回状态；获取平台数量及具体 `Info`。\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw05.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=bBKfuJusWU6LN4DyF7F8%2B5uPT6A%3D)\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw06.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=l9REme8bY%2BgkWl%2BI4AnaL2xCr2M%3D)\r\n\r\n\r\n#### 2. Device（设备）：\r\n- 实际的计算单元（GPU\u002FCPU\u002FFPGA 等）\r\n- **获取设备信息 (`clGetDeviceIDs`)**\r\n  - 类比：检查厨房里的锅具、刀具是否齐全\r\n  - 要点：根据 `Platform ID` 获取 `Device` 列表及设备详情（计算单元数、全局内存大小等）\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw07.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=2wkhSXx49RM7zFywZ5qNNrhkx%2BA%3D)\r\n\r\n\r\n#### 3. Context（上下文）：\r\n- 计算资源的管理容器，界定并行计算的资源范围\r\n- **创建上下文 (`clCreateContext`)**\r\n  - 类比：划定本次宴席可调用的资源范围\r\n  - 要点：基于特定 Device 创建，后续 `Queue`\u002F`Kernel` 均在此范围内管理资源，避免重复传参\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw08.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=TIpttSVGKjSheH8Zm0Mxqf0gnnE%3D)\r\n\r\n\r\n#### 4. Command Queue（命令队列）：\r\n- 任务调度器，实现流水线并行加速的关键数据结构\r\n- **创建命令队列 (`clCreateCommandQueue`)**\r\n  - 类比：建立传菜转盘\u002F工作流\r\n  - 要点：支持乱序执行属性，任务入队后自动被计算单元拾取\r\n\r\n\r\n\r\n#### 5. Program（程序）：\r\n- Kernel 源码编译后的内核程序对象\r\n- **编写与编译 Kernel (`clCreateProgramWithSource`)**\r\n  - 类比：准备并确认菜单\r\n  - **设计哲学**：为何运行时编译？→ 避免为每种设备预置编译器，厂商只需提供驱动，上层接口统一（类似工厂模式）\r\n  - 要点：源码以字符串形式传入，动态编译生成 `cl_program`；支持二进制缓存优化迁移\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw09.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=2ybTA%2BpvQqEAublfH4izg1FvT54%3D)\r\n\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw10.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=BacdCtFcF%2B64QLCrENJDT3Zpd%2BA%3D)\r\n\r\n\r\n#### 6. Kernel（内核）：\r\n- 实际执行的并行计算函数实例\r\n- **创建内核对象 (`clCreateKernel`)**\r\n  - 类比：将菜单分发给具体厨师，明确每人负责的任务\r\n  - 要点：Kernel 是 Program 的实例化，需指定工作组（Work Group）尺寸以实现并行分发\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw11.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=DIdtD%2BU1GMSSmokfvVGcXcnRRKU%3D)\r\n\r\n\r\n#### 7. 创建内存对象 (`clCreateBuffer` \u002F `clCreateImage`)\r\n- 类比：准备食材存放容器\r\n- 要点：支持 Buffer\u002FImage\u002FSVM 共享虚拟内存等多种类型\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw12.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=N9NIQKa9cgIhfufu%2B0yVnOuwkJY%3D)\r\n\r\n#### 8. 设置 Kernel 参数 (`clSetKernelArg`)：\r\n- 类比：告知厨师具体的口味要求\u002F细节指令\r\n- 要点：类似函数调用，但需通过专用接口传递参数给 Kernel 对象\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw13.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=AwsezafgQv8EZ06fHBboig%2BNTTo%3D)\r\n\r\n\r\n#### 9. 执行内核 (`clEnqueueNDRangeKernel`)\r\n- 类比：正式开火做菜\r\n- 要点：**ND Range** 定义三维网格维度，每个 Kernel 处理网格的一部分数据\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw14.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=W9k5hWjm3AlEWMOtpG2TAst9ssI%3D)\r\n\r\n\r\n#### 10. 主机和设备同步 (`clFinish` \u002F `event`)\r\n- 类比：确保菜品按顺序出锅，不乱套\r\n- 要点：`clFinish` 阻塞整个队列（简单粗暴）；`event` 机制支持精细化等待与依赖管理\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw15.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=jbM%2FfDgL9fiwdGw0CWFhyOp2PJc%3D)\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw16.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=Ye6yWu0bJW2RzFzKgApaWjm2pqk%3D)\r\n\r\n\r\n\r\n#### 11. 读取结果 (`clEnqueueReadBuffer`)\r\n- 类比：服务员从厨房端菜上桌\r\n- 要点：读取操作本身也是入队任务（Enqueue），需考虑中间结果依赖\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw17.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=e0Wf7Gadolw9xuWLBfzdCUluSNk%3D)\r\n\r\n\r\n\r\n#### 12. 释放资源 (`clRelease*`)\r\n- 类比：宴席结束，清洗归位\r\n- 要点：**尽早释放**，销毁顺序与创建相反；内部采用引用计数管理，计数归零且命令完成后自动删除\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw18.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=BbS%2Bxw3B1O08ceMmoffC7S3uoIQ%3D)\r\n\r\n\r\n下节课将从概念走向实战，针对高性能计算具体场景，手把手带你用 OpenCL 写出第一个并行程序！\r\n\r\n\r\n\r\n## 加入训练营\r\n#### 📺完整课程内容，请观看直播或查看课程回放：\r\n**InfiniTensor 官网**： https:\u002F\u002Fwww.infinitensor.com\r\n\r\n**B站直播**： InfiniTensor 官方直播间\r\n\r\n**视频号直播**： InfiniTensor 视频号预约\r\n\r\n**答疑交流**： 训练营官方社群⬇️\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002Fportal_news\u002F2026-xjq.png?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=RCGzL2mm8Hipb2jgTTOzg7DOtUs%3D)\r\n\r\n## 关注与交流\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002Fportal_news\u002Fnews_ewm02.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=ne2IbUxGKCs8rwPiAjr5B%2BpodTI%3D)",{"publishTime":7,"createTime":109,"canonicalPath":114,"id":115,"title":116},"\u002Fstudy-material\u002Fstudy-70","study-70","2026 夏季 InfiniTensor 训练营 CUDA 编程 2：《性能模型与逐元素优化》",38,"\u002Fstudy-material\u002Fstudy-71","study-71","markdown",{"publishTime":7,"createTime":109,"canonicalPath":122,"id":123,"title":124},"\u002Fstudy-material\u002Fstudy-72","study-72","2026 夏季 InfiniTensor 训练营通信与并行 2：《大模型并行策略与通信优化》",{"htmlContent":126,"headings":127},"\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw01.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=rgfq5bAXaJ1HY7cMxuoxCoyD%2Fx0%3D\" alt=\"\">\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size:12px;color:#555;\">7 月 21 日，2026 夏季 InfiniTensor 训练营 OpenCL 编程方向第一课《OpenCL 概述与运行时》开讲。\u003Cbr>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>本节课作为 OpenCL 系列课程的开篇，将帮大家建立对 OpenCL 的正确认知。从“为什么要学”出发，通过生动的类比，拆解 OpenCL 看似复杂的运行时流程，为后续的实战课程打下坚实基础。\u003C\u002Fp>\n\u003Ch2 id=\"认识-opencl\">\u003Ca class=\"anchor\" href=\"#认识-opencl\" aria-label=\"跳转到标题：认识 OpenCL\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>认识 OpenCL\u003C\u002Fh2>\u003Ch3 id=\"什么是-opencl\">\u003Ca class=\"anchor\" href=\"#什么是-opencl\" aria-label=\"跳转到标题：什么是 OpenCL？\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>什么是 OpenCL？\u003C\u002Fh3>\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw02.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=h0ngMWXHc62SNH1I%2BXt5g7cRRLQ%3D\" alt=\"\">\u003C\u002Fp>\n\u003Col>\n\u003Cli>全称：Open Computing Language\u003C\u002Fli>\n\u003Cli>本质：为异构平台提供统一并行编程框架的开放标准\u003C\u002Fli>\n\u003Cli>核心能力：通过统一 API 支持 CPU、GPU、FPGA、NPU 等混合设备并行计算\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Ch3 id=\"为什么要学-opencl-而不是直接学-cuda\">\u003Ca class=\"anchor\" href=\"#为什么要学-opencl-而不是直接学-cuda\" aria-label=\"跳转到标题：为什么要学 OpenCL 而不是直接学 CUDA？\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>为什么要学 OpenCL 而不是直接学 CUDA？\u003C\u002Fh3>\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw03.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=so%2F44weBJUhJN27fDpu2DH6ar98%3D\" alt=\"\">\u003C\u002Fp>\n\u003Col>\n\u003Cli>\u003Cstrong>跨平台优势\u003C\u002Fstrong>：一套代码适配多厂商硬件（NVIDIA\u002FAMD\u002FIntel\u002F高通等），牺牲极致性能换取通用性与可移植性\u003C\u002Fli>\n\u003Cli>\u003Cstrong>低门槛与低成本\u003C\u002Fstrong>：不依赖昂贵的高端显卡，低端设备甚至 CPU（支持超线程\u002FOpenCL 驱动）即可开发验证\u003C\u002Fli>\n\u003Cli>\u003Cstrong>关注并行本质\u003C\u002Fstrong>：相比 CUDA 的设备绑定，OpenCL 更侧重于并行计算思维本身的训练\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Ch3 id=\"端侧部署的现实需求\">\u003Ca class=\"anchor\" href=\"#端侧部署的现实需求\" aria-label=\"跳转到标题：端侧部署的现实需求\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>端侧部署的现实需求\u003C\u002Fh3>\u003Col>\n\u003Cli>\u003Cstrong>云侧痛点\u003C\u002Fstrong>：集群建设成本高、网络延迟、隐私泄露风险\u003C\u002Fli>\n\u003Cli>\u003Cstrong>端侧优势\u003C\u002Fstrong>：隐私性强、成本可控、Token 消耗无压力（Agent 应用友好）\u003C\u002Fli>\n\u003Cli>\u003Cstrong>算力现状\u003C\u002Fstrong>：端侧加速卡碎片化严重，OpenCL 是解决“多设备适配”的最优解之一\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Ch2 id=\"opencl-程序\">\u003Ca class=\"anchor\" href=\"#opencl-程序\" aria-label=\"跳转到标题：OpenCL 程序\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>OpenCL 程序\u003C\u002Fh2>\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw04.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=h8zpQZiq8c3ZTywf2YjioS%2BrpoY%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch4 id=\"1-platform-平台\">\u003Ca class=\"anchor\" href=\"#1-platform-平台\" aria-label=\"跳转到标题：1. Platform（平台）：\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>1. Platform（平台）：\u003C\u002Fh4>\u003Cul>\n\u003Cli>OpenCL 实现提供者提供的软件抽象层，用于管理一组 OpenCL 设备，通常由硬件厂商驱动或第三方 OpenCL 实现提供，例如 NVIDIA、Intel 等\u003C\u002Fli>\n\u003Cli>\u003Cstrong>获取平台信息 (\u003Ccode>clGetPlatformIDs\u003C\u002Fcode>)\u003C\u002Fstrong>\u003Cul>\n\u003Cli>类比：确定宴席举办地点\u003C\u002Fli>\n\u003Cli>要点：C 语言风格 API，需检查返回状态；获取平台数量及具体 \u003Ccode>Info\u003C\u002Fcode>。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw05.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=bBKfuJusWU6LN4DyF7F8%2B5uPT6A%3D\" alt=\"\">\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw06.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=l9REme8bY%2BgkWl%2BI4AnaL2xCr2M%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch4 id=\"2-device-设备\">\u003Ca class=\"anchor\" href=\"#2-device-设备\" aria-label=\"跳转到标题：2. Device（设备）：\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>2. Device（设备）：\u003C\u002Fh4>\u003Cul>\n\u003Cli>实际的计算单元（GPU\u002FCPU\u002FFPGA 等）\u003C\u002Fli>\n\u003Cli>\u003Cstrong>获取设备信息 (\u003Ccode>clGetDeviceIDs\u003C\u002Fcode>)\u003C\u002Fstrong>\u003Cul>\n\u003Cli>类比：检查厨房里的锅具、刀具是否齐全\u003C\u002Fli>\n\u003Cli>要点：根据 \u003Ccode>Platform ID\u003C\u002Fcode> 获取 \u003Ccode>Device\u003C\u002Fcode> 列表及设备详情（计算单元数、全局内存大小等）\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw07.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=2wkhSXx49RM7zFywZ5qNNrhkx%2BA%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch4 id=\"3-context-上下文\">\u003Ca class=\"anchor\" href=\"#3-context-上下文\" aria-label=\"跳转到标题：3. Context（上下文）：\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>3. Context（上下文）：\u003C\u002Fh4>\u003Cul>\n\u003Cli>计算资源的管理容器，界定并行计算的资源范围\u003C\u002Fli>\n\u003Cli>\u003Cstrong>创建上下文 (\u003Ccode>clCreateContext\u003C\u002Fcode>)\u003C\u002Fstrong>\u003Cul>\n\u003Cli>类比：划定本次宴席可调用的资源范围\u003C\u002Fli>\n\u003Cli>要点：基于特定 Device 创建，后续 \u003Ccode>Queue\u003C\u002Fcode>\u002F\u003Ccode>Kernel\u003C\u002Fcode> 均在此范围内管理资源，避免重复传参\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw08.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=TIpttSVGKjSheH8Zm0Mxqf0gnnE%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch4 id=\"4-command-queue-命令队列\">\u003Ca class=\"anchor\" href=\"#4-command-queue-命令队列\" aria-label=\"跳转到标题：4. Command Queue（命令队列）：\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>4. Command Queue（命令队列）：\u003C\u002Fh4>\u003Cul>\n\u003Cli>任务调度器，实现流水线并行加速的关键数据结构\u003C\u002Fli>\n\u003Cli>\u003Cstrong>创建命令队列 (\u003Ccode>clCreateCommandQueue\u003C\u002Fcode>)\u003C\u002Fstrong>\u003Cul>\n\u003Cli>类比：建立传菜转盘\u002F工作流\u003C\u002Fli>\n\u003Cli>要点：支持乱序执行属性，任务入队后自动被计算单元拾取\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch4 id=\"5-program-程序\">\u003Ca class=\"anchor\" href=\"#5-program-程序\" aria-label=\"跳转到标题：5. Program（程序）：\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>5. Program（程序）：\u003C\u002Fh4>\u003Cul>\n\u003Cli>Kernel 源码编译后的内核程序对象\u003C\u002Fli>\n\u003Cli>\u003Cstrong>编写与编译 Kernel (\u003Ccode>clCreateProgramWithSource\u003C\u002Fcode>)\u003C\u002Fstrong>\u003Cul>\n\u003Cli>类比：准备并确认菜单\u003C\u002Fli>\n\u003Cli>\u003Cstrong>设计哲学\u003C\u002Fstrong>：为何运行时编译？→ 避免为每种设备预置编译器，厂商只需提供驱动，上层接口统一（类似工厂模式）\u003C\u002Fli>\n\u003Cli>要点：源码以字符串形式传入，动态编译生成 \u003Ccode>cl_program\u003C\u002Fcode>；支持二进制缓存优化迁移\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw09.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=2ybTA%2BpvQqEAublfH4izg1FvT54%3D\" alt=\"\">\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw10.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=BacdCtFcF%2B64QLCrENJDT3Zpd%2BA%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch4 id=\"6-kernel-内核\">\u003Ca class=\"anchor\" href=\"#6-kernel-内核\" aria-label=\"跳转到标题：6. Kernel（内核）：\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>6. Kernel（内核）：\u003C\u002Fh4>\u003Cul>\n\u003Cli>实际执行的并行计算函数实例\u003C\u002Fli>\n\u003Cli>\u003Cstrong>创建内核对象 (\u003Ccode>clCreateKernel\u003C\u002Fcode>)\u003C\u002Fstrong>\u003Cul>\n\u003Cli>类比：将菜单分发给具体厨师，明确每人负责的任务\u003C\u002Fli>\n\u003Cli>要点：Kernel 是 Program 的实例化，需指定工作组（Work Group）尺寸以实现并行分发\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw11.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=DIdtD%2BU1GMSSmokfvVGcXcnRRKU%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch4 id=\"7-创建内存对象-clcreatebuffer-clcreateimage\">\u003Ca class=\"anchor\" href=\"#7-创建内存对象-clcreatebuffer-clcreateimage\" aria-label=\"跳转到标题：7. 创建内存对象 (clCreateBuffer \u002F clCreateImage)\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>7. 创建内存对象 (\u003Ccode>clCreateBuffer\u003C\u002Fcode> \u002F \u003Ccode>clCreateImage\u003C\u002Fcode>)\u003C\u002Fh4>\u003Cul>\n\u003Cli>类比：准备食材存放容器\u003C\u002Fli>\n\u003Cli>要点：支持 Buffer\u002FImage\u002FSVM 共享虚拟内存等多种类型\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw12.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=N9NIQKa9cgIhfufu%2B0yVnOuwkJY%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch4 id=\"8-设置-kernel-参数-clsetkernelarg\">\u003Ca class=\"anchor\" href=\"#8-设置-kernel-参数-clsetkernelarg\" aria-label=\"跳转到标题：8. 设置 Kernel 参数 (clSetKernelArg)：\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>8. 设置 Kernel 参数 (\u003Ccode>clSetKernelArg\u003C\u002Fcode>)：\u003C\u002Fh4>\u003Cul>\n\u003Cli>类比：告知厨师具体的口味要求\u002F细节指令\u003C\u002Fli>\n\u003Cli>要点：类似函数调用，但需通过专用接口传递参数给 Kernel 对象\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw13.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=AwsezafgQv8EZ06fHBboig%2BNTTo%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch4 id=\"9-执行内核-clenqueuendrangekernel\">\u003Ca class=\"anchor\" href=\"#9-执行内核-clenqueuendrangekernel\" aria-label=\"跳转到标题：9. 执行内核 (clEnqueueNDRangeKernel)\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>9. 执行内核 (\u003Ccode>clEnqueueNDRangeKernel\u003C\u002Fcode>)\u003C\u002Fh4>\u003Cul>\n\u003Cli>类比：正式开火做菜\u003C\u002Fli>\n\u003Cli>要点：\u003Cstrong>ND Range\u003C\u002Fstrong> 定义三维网格维度，每个 Kernel 处理网格的一部分数据\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw14.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=W9k5hWjm3AlEWMOtpG2TAst9ssI%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch4 id=\"10-主机和设备同步-clfinish-event\">\u003Ca class=\"anchor\" href=\"#10-主机和设备同步-clfinish-event\" aria-label=\"跳转到标题：10. 主机和设备同步 (clFinish \u002F event)\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>10. 主机和设备同步 (\u003Ccode>clFinish\u003C\u002Fcode> \u002F \u003Ccode>event\u003C\u002Fcode>)\u003C\u002Fh4>\u003Cul>\n\u003Cli>类比：确保菜品按顺序出锅，不乱套\u003C\u002Fli>\n\u003Cli>要点：\u003Ccode>clFinish\u003C\u002Fcode> 阻塞整个队列（简单粗暴）；\u003Ccode>event\u003C\u002Fcode> 机制支持精细化等待与依赖管理\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw15.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=jbM%2FfDgL9fiwdGw0CWFhyOp2PJc%3D\" alt=\"\">\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw16.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=Ye6yWu0bJW2RzFzKgApaWjm2pqk%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch4 id=\"11-读取结果-clenqueuereadbuffer\">\u003Ca class=\"anchor\" href=\"#11-读取结果-clenqueuereadbuffer\" aria-label=\"跳转到标题：11. 读取结果 (clEnqueueReadBuffer)\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>11. 读取结果 (\u003Ccode>clEnqueueReadBuffer\u003C\u002Fcode>)\u003C\u002Fh4>\u003Cul>\n\u003Cli>类比：服务员从厨房端菜上桌\u003C\u002Fli>\n\u003Cli>要点：读取操作本身也是入队任务（Enqueue），需考虑中间结果依赖\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw17.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=e0Wf7Gadolw9xuWLBfzdCUluSNk%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch4 id=\"12-释放资源-clrelease\">\u003Ca class=\"anchor\" href=\"#12-释放资源-clrelease\" aria-label=\"跳转到标题：12. 释放资源 (clRelease*)\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>12. 释放资源 (\u003Ccode>clRelease*\u003C\u002Fcode>)\u003C\u002Fh4>\u003Cul>\n\u003Cli>类比：宴席结束，清洗归位\u003C\u002Fli>\n\u003Cli>要点：\u003Cstrong>尽早释放\u003C\u002Fstrong>，销毁顺序与创建相反；内部采用引用计数管理，计数归零且命令完成后自动删除\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_71_zw18.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=BbS%2Bxw3B1O08ceMmoffC7S3uoIQ%3D\" alt=\"\">\u003C\u002Fp>\n\u003Cp>下节课将从概念走向实战，针对高性能计算具体场景，手把手带你用 OpenCL 写出第一个并行程序！\u003C\u002Fp>\n\u003Ch2 id=\"加入训练营\">\u003Ca class=\"anchor\" href=\"#加入训练营\" aria-label=\"跳转到标题：加入训练营\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>加入训练营\u003C\u002Fh2>\u003Ch4 id=\"完整课程内容-请观看直播或查看课程回放\">\u003Ca class=\"anchor\" href=\"#完整课程内容-请观看直播或查看课程回放\" aria-label=\"跳转到标题：📺完整课程内容，请观看直播或查看课程回放：\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>📺完整课程内容，请观看直播或查看课程回放：\u003C\u002Fh4>\u003Cp>\u003Cstrong>InfiniTensor 官网\u003C\u002Fstrong>： \u003Ca href=\"https:\u002F\u002Fwww.infinitensor.com\">https:\u002F\u002Fwww.infinitensor.com\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>B站直播\u003C\u002Fstrong>： InfiniTensor 官方直播间\u003C\u002Fp>\n\u003Cp>\u003Cstrong>视频号直播\u003C\u002Fstrong>： InfiniTensor 视频号预约\u003C\u002Fp>\n\u003Cp>\u003Cstrong>答疑交流\u003C\u002Fstrong>： 训练营官方社群⬇️\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002Fportal_news\u002F2026-xjq.png?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=RCGzL2mm8Hipb2jgTTOzg7DOtUs%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch2 id=\"关注与交流\">\u003Ca class=\"anchor\" href=\"#关注与交流\" aria-label=\"跳转到标题：关注与交流\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>关注与交流\u003C\u002Fh2>\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002Fportal_news\u002Fnews_ewm02.jpg?Expires=1792752590&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=ne2IbUxGKCs8rwPiAjr5B%2BpodTI%3D\" alt=\"\">\u003C\u002Fp>\n",[128,131,134,137,139,142,146,149,152,155,158,161,164,167,170,173,176,179,181,184],{"id":129,"text":130,"level":110},"认识-opencl","认识 OpenCL",{"id":132,"text":133,"level":9},"什么是-opencl","什么是 OpenCL？",{"id":135,"text":136,"level":9},"为什么要学-opencl-而不是直接学-cuda","为什么要学 OpenCL 而不是直接学 CUDA？",{"id":138,"text":138,"level":9},"端侧部署的现实需求",{"id":140,"text":141,"level":110},"opencl-程序","OpenCL 程序",{"id":143,"text":144,"level":145},"1-platform-平台","1. Platform（平台）：",4,{"id":147,"text":148,"level":145},"2-device-设备","2. Device（设备）：",{"id":150,"text":151,"level":145},"3-context-上下文","3. Context（上下文）：",{"id":153,"text":154,"level":145},"4-command-queue-命令队列","4. Command Queue（命令队列）：",{"id":156,"text":157,"level":145},"5-program-程序","5. Program（程序）：",{"id":159,"text":160,"level":145},"6-kernel-内核","6. Kernel（内核）：",{"id":162,"text":163,"level":145},"7-创建内存对象-clcreatebuffer-clcreateimage","7. 创建内存对象 (clCreateBuffer \u002F clCreateImage)",{"id":165,"text":166,"level":145},"8-设置-kernel-参数-clsetkernelarg","8. 设置 Kernel 参数 (clSetKernelArg)：",{"id":168,"text":169,"level":145},"9-执行内核-clenqueuendrangekernel","9. 执行内核 (clEnqueueNDRangeKernel)",{"id":171,"text":172,"level":145},"10-主机和设备同步-clfinish-event","10. 主机和设备同步 (clFinish \u002F event)",{"id":174,"text":175,"level":145},"11-读取结果-clenqueuereadbuffer","11. 读取结果 (clEnqueueReadBuffer)",{"id":177,"text":178,"level":145},"12-释放资源-clrelease","12. 释放资源 (clRelease*)",{"id":180,"text":180,"level":110},"加入训练营",{"id":182,"text":183,"level":145},"完整课程内容-请观看直播或查看课程回放","📺完整课程内容，请观看直播或查看课程回放：",{"id":185,"text":185,"level":110},"关注与交流"]