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如何评价摩尔线程发布基于 MUSA 统一系统架构发布的 GPU? - 知乎

如何评价摩尔线程发布基于 MUSA 统一系统架构发布的 GPU? - 知乎首页知乎知学堂发现等你来答切换模式登录/注册NVIDIA（英伟达）图形处理器（GPU）芯片（集成电路）芯片设计如何评价摩尔线程发布基于 MUSA 统一系统架构发布的 GPU?[文章: 12nm！摩尔线程发布：全功能GPU芯片“苏堤”！发布：桌面2048核心、云端4096核心显卡！]显示全部关注者347被浏览436,158关注问题写回答邀请回答好问题 363 条评论分享24 个回答默认排序陈巍大模型/存算一体/GPGPU 关注据说使用了imagination的PowerVR IP核（猜测是GPU IP核与NNA IP核），但是GPU核心专利还在别人手上，国产GPU创企同质化竞争的时代开启（2000字长文解读）PowerVR GPU与NNA（NPU）整合架构PowerVR GPU架构1 据说使用了imagination的PowerVR IP核具体用的哪一款IP，后面会给大家做技术分析。因为PowerVR的IP族是包括硬核的，也就是说，连后端版图都不需要自己做。所以18个月上市，对使用外购IP核心的产品，也在合理的研发周期内。至于说这么多产业合作方，应该有部分也有imagination的功劳在。支持DirectX和vulkun，能看的出来imagination这些年一直对桌面GPU虎视眈眈。imagination的生态适配与合作好像摩尔线程也没说都是自己自研的，这种模式在GPU产业界也是司空见惯。毕竟能自研GPU核心的，世界上没几家。国内大概还有好些家创企，是买了imagination的IP核打造GPU。2 GPU核心专利还在别人手上按理说，看到国产GPU的进步，我们应该高兴。毕竟只要是进步，就是有意义的。但作为产业来说，如果还被别人掐着脖子的进步，始终还是有性命之忧。我们去年做过GPU专利的分析（是GPU相关的专利，需要注意GPU厂家的专利不全是GPU专利，也会有些杂七杂八的非GPU专利），国内只有华为拼了命挤进前15，好歹有个2位数的专利。国内其他厂商，追赶的道路还很漫长。而GPU领域的核心专利，特别是Rendor/DirectX之类的显示专利，主要在NVIDIA、Intel、AMD之类的大厂手中。国内的厂家，基本没法绕过去。别人掐着脖子，就意味着，你能不能用，要听Vendor爸爸的。你卖的产品，要么一次性给钱，要么给Vendor分钱。3 这样的模式好不好？1）从纯商业运作来说，这样的模式是很对的。例如，使用ARM核和生态打造MCU也是非常正常的事情，很少有MCU厂家有自研核心的资源和体量。搞钱嘛，就得找最快最小代价的路线。2）从国产替代来说呢，长期使用国外厂家的GPU核心，是不利于自主知识产权技术的发展的。一旦多方对峙，就很有可能出现没支持没法用的情况，这无论对于GPU厂商还是GPU客户都是很大的生存风险。比如前段时间的ARM断供俄罗斯，就闹的沸沸扬扬。记得刚保送研究生的时候，学校里的老教授给我们介绍清华微电子所在90年代取得的成绩，其中一个就是媲美intel 486的CPU芯片。清华做出来之后，美国就解除了对486 CPU的禁运，然后清华这一本来可以量产的“CPU成果”就被束之高阁。如果那时一直做下去，中国现在又何愁没有自己的intel和NVIDIA？3）从技术来说，期待有更多的国内芯片企业加入到核心IP的自研，让GPU和算力芯片领域真正做到核心技术的百花齐放。4 国产GPU创企内卷时代的开启目前国内GPU创企，从头开始做GPU内核的不多。一般来说会走两条路：1）使用imagination或别家的GPU IP核做GPU这样的路径无外乎就是买GPU IP核，买Design Service，只要有钱，Vendor都帮你配好，就好像网游里买装备。反正家里不差钱，一句话买买买。至于说DirectX适配，玩视频游戏，只要给够钱，自己再努努力，都能搞定。代价呢，就是核心的电路和专利都不是自己的，这电路为什么这么设计可能也不知道。将来想升级的时候得看Vendor愿不愿意卖。2）使用开源的NVDLA IP核做GPGPU另一类路径，就是借助NVIDIA开源的NVDLA。反正代码和SDK都开源，拿过来改改，攒一个算力更大的没啥问题，边做边学。代价就是生态上没有买的轻松，什么适配都得自己摸石头过活。这两个都是GPU技术迭代的正常路线。如果只有两家这么干，大家也会活得挺舒服。但是，考虑到国内的GPU创企保守统计已经超过了25家，那这25家里大部分都是用imagination或者NVDLA的IP核，用的GPU核心差不多，就会面临严重的同质化竞争问题，很难有自己的核心壁垒。换句话说，对于摩尔线程GPU勾搭的客户和合作，芯动的GPU做对应市场的替换也会挺快。大家的主航道还没有成型，却都还没建立自己的护城河。（护城河在imagination手里啊）将近20多家GPU在信创/国产替代这个不大的市场里互相抢客户，严重的GPU赛道内卷，对投资机构来说并不是什么好消息。你卖包子我也卖包子，大部分包子馅不是紫的（imagination）就是绿的（NVDLA）。希望在GPU赛道，不要是淘金的亏了，卖水的赚了。这时候，就需要有人顶住困难，做核心技术。也需要有人做超越GPU的技术。5 结语作为产业里的人，不管是做技术的还是玩资本的，当你老去的时候，你会希望你的后代重复我们走过的路，在关键科技上被人卡脖子吗？还是要祝贺摩尔线程取得的进步，不管怎么说，都是GPU产业的有益尝试。更多的企业参GPU研发，才会培养更多的人才，中国的GPU产业才会有更多可能。相关推荐编辑于 2022-05-31 23:07赞同 21731 条评论分享收藏喜欢收起CompilerCoderGPU编译器工程师关注行业相关，一直从事图形编译器的工作，包括dx/ogl/vukuan的支持。不过由于是友商，不做过多评价。单从图形方面来说没那么简单，下面详细说说图形编译器方面需要支持的内容。要支持dx/ogl/vulkuan还是有很多工作要做的，具体的工作内容可参见之前的回答。这篇是一个补充。要支持dx就有很多内容要做，因为微软实在太坑了。完全支持dx算的上支持三套系统了。dx9算一套，dx10/11算一套，dx12算一套。1.dx9单从编译器方面来说dx9算一套，下面是微软dx9 shader相关的asm，可以看到这些指令相对较少了，支持起来可以说非常简单了。2.dx10/11dx10 shader相关的asmdx11 shader相关的asmdx10/11的格式基本相同，与dx9会有区别。而且dx10/11增加了很多特性，不但硬件需要支持，软件也要配套跟上，这一块内容相对dx9来说多的多，支持起来也不是那么容易。3.dx12之所以说微软巨坑就是dx12又完全丢掉之前的重新搞了一套新的格式，相当与之前的全部清零，工作量又要增加了。dx12用的dxil，llvm ir的一个子集。再来说ogl/oesogl的一些版本：oes的一些版本：spirv：ogl/oes相比dx来说好多了，因为没有定义自己的asm，可以厂商自己定义。vulkan定义了一套spirv，一般来说编译器支持spirv就可以了。不过spirv也有一些不能完全表达ogl shader相关的地方，这个就不具体说了。以上只是编译器相关的内容，如果加上驱动、硬件三者配合内容还是挺多的，短期能够做好并不容易。如果再加上AI，内容就更多了。我司支持dx/ogl/vulkuan最新版本，已流片多款GPU芯片。有对编译器、操作系统内核编程、GPU硬件相关岗位感兴趣的朋友欢迎联系或一起聊天。各种硬核知识欢迎你来挑战。发布于 2022-06-03 13:04赞同 3811 条评论分享收藏喜欢

摩尔线程：MUSA/MUSIFY不涉英伟达EULA相关条款，开发者可放心使用|源代码|musa|英伟达eu|musify_网易订阅

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摩尔线程：MUSA/MUSIFY不涉英伟达EULA相关条款，开发者可放心使用

2024-03-05 20:34:52　来源: 界面新闻

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3月5日，摩尔线程发布声明称，MUSA/MUSIFY不涉及英伟达EULA相关条款，开发者可放心使用。声明指出，MUSA是摩尔线程自主研发、拥有全部知识产权、软硬一体的全功能GPU先进计算统一系统架构，与CUDA无任何依赖关系。MUSIFY是摩尔线程面向广大MUSA开发者提供的开发工具，方便用户在MUSA计算平台上进行应用移植与开发，可以让开发者将自己的C++源代码，转换成MUSA C++源代码，再通过MUSA编译器MCC编译生成基于MUSA指令集的二进制代码，最终运行在摩尔线程全功能GPU上。

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自研MUSA架构！摩尔线程发布4096核心服务器GPU，还有桌面级显卡_腾讯新闻

自研MUSA架构！摩尔线程发布4096核心服务器GPU，还有桌面级显卡

摘要：2022年3月30日，北京——摩尔线程今天举行主题为“元动力创无限”的春季发布会。摩尔线程创始人兼CEO张建中解读了“元计算”这一产业趋势，并发布全新架构及系列重磅新品，包括：MUSA（Moore Threads Unified System Architecture）统一系统架构；基于MUSA架构打造的第一代多功能GPU芯片苏堤；面向PC和工作站的桌面级显卡MTT S60和专为数据中心打造的图形渲染和计算卡 MTT S2000；GPU物理引擎AlphaCore ；DIGITALME数字人解决方案；及助力数字经济发展的多个元计算应用解决方案。

2022年3月30日，北京——摩尔线程今天举行主题为“元动力创无限”的春季发布会。摩尔线程创始人兼CEO张建中解读了“元计算”这一产业趋势，并发布全新架构及系列重磅新品，包括：MUSA（Moore Threads Unified System Architecture）统一系统架构；基于MUSA架构打造的第一代多功能GPU芯片苏堤；面向PC和工作站的桌面级显卡MTT S60和专为数据中心打造的图形渲染和计算卡MTT S2000；GPU物理引擎AlphaCore ；DIGITALME数字人解决方案；及助力数字经济发展的多个元计算应用解决方案。

发布会现场，摩尔线程还演示了基于其MUSA架构多功能GPU的丰富应用，覆盖数字办公、影音娱乐、工业和建筑设计、地理信息系统、云桌面、云游戏等多个场景，充分展示了摩尔线程产品的广泛应用性，以及为数字经济加速提供的强劲动力。来自政府、高校、开发者、生态合作伙伴和行业客户以及媒体的众多嘉宾，共同见证了摩尔线程这一重要时刻。

“元计算”赋能下一代互联网

摩尔线程首次提出“元计算”这一概念。元计算是支撑包括元宇宙在内的下一代互联网应用的通用算力平台，以图形计算和AI计算为基石，是物理世界数字化和数字世界物理化的底层算力支撑，将为数字经济开辟更广阔的发展空间。

摩尔线程创始人兼CEO张建中表示：“元计算时代已然开启，多功能GPU是元计算的算力基础设施，也是我们创新的原点。摩尔线程致力于面向元计算应用的新一代GPU创新，构建融合视觉计算、3D图形计算、科学计算及人工智能计算的通用计算平台，建立基于云原生GPU计算的生态系统，助力数字经济发展。此次系列新品的发布，是公司发展的重大里程碑，更是我们研发实力、生态凝聚力和创新执行力的集中体现。”

MUSA统一系统架构及第一代芯片“苏堤”

MUSA是摩尔线程产品系列采用的统一系统架构，包括统一的编程模型、软件运行库、驱动程序框架、指令集架构和芯片架构。开发者基于MUSA开发的应用将具备广泛的可移植性，可以同时运行在云端和边缘的众多计算平台上，包括面向图形、计算、多媒体和人工智能的各类产品线。

与此同时，基于MUSA统一系统架构打造的第一代摩尔线程多功能GPU芯片——苏堤正式亮相。芯片内置现代图形渲染引擎、智能多媒体引擎、AI计算加速引擎、物理仿真及科学计算四大引擎，旨在以先进的现代GPU架构、广泛的平台通用性和全栈计算能力，充分满足数字经济云边端多元算力需求。至此，凭借对GPU市场的深刻洞察、久经验证的GPU设计成功经验、严谨成熟的技术路线和强大的执行力，摩尔线程成为目前中国市场率先进行多功能GPU研发设计、并能以极快速度实现GPU量产交付的公司。

下一代多平台GPU物理引擎AlphaCore

AlphaCore 是由摩尔线程独立设计研发的下一代多平台GPU物理仿真系统，能够对物理世界中复杂的固体、柔性体、流体等效果进行超高精度的物理仿真处理，通过运算模拟，让布料、毛发和数字角色软体肌肉组织的物理交互效果达到电影级别般真实。

AlphaCore 物理引擎凭借强大的材料力学模块，可以实现丰富的材料交互动态效果，例如：弹塑性材料、各项异性材料、羽绒服、皮革、丝绸、绵纶等。基于AlphaCore开发的系列工具包括：布料毛发制作工具——VeraFiber；气体流体仿真工具——Catalyst；以及生物仿生计算工具——Bionics。对比Houdini Vellum 的软体毛发布料和PyroFX 的烟火流体， AlphaCore 均有 5~10倍的性能提升。

同时，AlphaCore也提供了多平台兼容版本，以最大程度兼容现有生态中的Vulkan、CUDA、DirectX等 Runtime API环境，及Houdini，Unreal，Unity和D5游戏引擎和设计软件，广泛覆盖影视后期制作、动画、游戏、建筑表现等领域的实际应用场景。

面向PC和工作站的桌面级显卡MTT S60

发布会上，基于MUSA统一系统架构的摩尔线程全新第一代桌面级显卡MTT S60首发，成为全场焦点。作为摩尔线程首款突破性多功能智能显卡，MTT S60显卡主要面向PC和工作站，凭借其优秀的主流图形能力、广泛的AI算法支持、突破性的视频处理能力、以及独特的绿色能效技术，能够为图形渲染、数字办公、影音娱乐、智能制造CAD/CAE、地理信息GIS、建筑设计BIM、视频编辑、人工智能应用以及主流游戏等娱乐需求提供强劲算力支持。

MTT S60显卡基于MUSA统一系统架构GPU苏堤核心晶片制成，采用12nm制程，包含2048个MUSA核心，单精度浮点运算最高可达6TFLOPS，像素填充率为192G Pixel/s，搭载8GB显存，支持4K/8K高清显示。MTT S60显卡不仅支持主流的H.264和H.265编码格式，还领先业内同类产品提供对AV1视频格式的硬件编码支持；而在硬件解码方面，则支持 AV1、H.264、H.265等诸多格式的硬件解码。不仅如此，MTT S60显卡还支持DirectX、Vulkan、OpenGL和OpenGL ES等众多图形API接口，可满足各类高图形负载应用对2D和3D图形渲染的需求。

MTT S60的推出使得摩尔线程成为率先支持Windows10操作系统的GPU公司。MTT S60显卡优异的图形性能亦可满足电子竞技用户的电子竞技游戏需求。不仅可以在Windows10操作系统、1080P分辨率、最高画质环境下为《英雄联盟》电子竞技玩家提供流畅游戏体验，也可以在国产Linux操作系统环境下，完成《反恐精英：全球攻势》、《刀塔2》等多款热门游戏的流畅运行。

目前，摩尔线程MTT S60支持英特尔、AMD、龙芯、飞腾、兆芯等主流CPU以及Windows、麒麟、统信、Ubuntu等操作系统，并且已经着手与众多PC合作伙伴开展合作，包括联想、浪潮、长城超云等（排名不分先后）。与此同时，多家合作伙伴基于MTT S60显卡打造的行业应用在现场进行了演示，包括：金山办公、小鱼易连、太极图形、中望CAD、广联达、D5、苍穹数码、超图软件、易智瑞、中地数码、OSG社区和Gala Sports等。

生态协作始终是推动产业和体验升级的关键所在。因此，摩尔线程发起并携手众多行业合作伙伴共建中国“完美体验系统联盟（PES联盟）”,旨在通过产品规划、研发、最终生产阶段的协同合作，聚焦统一标准、整合资源、分享技术等，为生态伙伴创造更多价值，为终端用户打造完美体验。

专为数据中心打造的MTT S2000

摩尔线程基于MUSA统一系统架构苏堤核心晶片打造的数据中心级多功能GPU产品MTT S2000，同样引人注目。摩尔线程MTT S2000内置渲染、音视频编解码、人工智能加速和并行计算等硬件模块，能够提供图形图像渲染、视频云处理、AI和科学计算在内的全栈功能。凭借其独特的渲染、虚拟化等能力和广泛的生态支持，MTT S2000可以在云桌面、安卓云游戏、视频云、云渲染和AI推理计算加速等应用场景全面助力绿色数字经济发展。

MTT S2000采用12nm制程，使用4096个MUSA核心，最大配置32GB显存，单精度算力最高可达到12TFlops，支持H.264、H.265、AV1多路高清视频编解码，以及广泛的AI模型算法加速，支持PyTorch、Tensorflow、PaddlePaddle等主流深度学习框架。为提升MUSA架构产品在实际生产环境中的表现，摩尔线程还为MTT S2000系列产品推出了针对硬件架构进行专门优化的统一编程模型、运行库、驱动等软件工具，可方便开发人员完成应用的移植和适配，充分调用MTT S2000的硬件资源和算力。MTT S2000支持OpenGL、OpenGL ES、DirectX、Vulkan等图形API；通过FFMPEG和VA-API/DXVA等兼容支持音视频处理生态；并通过OpenCL及Vulkan满足AI和科学计算的程序兼容。

目前，摩尔线程MTT S2000已支持x86和ARM架构CPU，服务器合作伙伴包括浪潮、新华三、联想、清华同方、长城超云、思腾合力等OEM（排名不分先后）。

现场还宣布了摩尔线程将与蔚领时代、声网和一流科技等在云游戏、音视频编解码和异构分布式计算方面的合作伙伴共同投入研发，携手建设生态，打造最优化的行业解决方案。此外，摩尔线程还与浪潮展开了元脑生态的战略合作，共同推进产业AI化的发展。

元计算解决方案助力数字经济

基于摩尔线程多功能GPU的核心算力，面向复杂的实际应用场景，摩尔线程正携手诸多合作伙伴打造各行业元计算解决方案，以算力支撑为数字经济的加速发展贡献力量。

数字能源，推进智能应用——摩尔线程与国网电商科技共同推进“电力行业人工智能”及“工业元宇宙电力场景”应用。双方共建智能计算芯片联合应用研究实验室，探索和推进GPU芯片在电力领域的应用，支撑新型能源电力系统建设中软硬件基础需求，实现双碳高性能智能计算平台建设、应用与推广。

数字农业，助力乡村振兴——摩尔线程与埃舍尔科技共同打造数字化示范种植基地，构建农业基地数字孪生模型，全面实现标准化智慧化管理，为产品加工的全流程保驾护航。通过数字化种植实现品种溯源，保障品种优质优价，科学指导轮作能力，推动农村数字化、标准化、规模化的全新发展趋势。

数字城市，推动政企转型——面向大数据的GPU通用计算、高清视频处理以及GPU建模和 3D渲染能力，可以在时间和空间维度把物理世界的数据快速传递到数字孪生世界，推动政企数字化转型，促进经济发展。摩尔线程正在与光线云和51 World正在云原生渲染和数字孪生方面进行探索。

数字生命，助力科学探索——冷冻电镜蛋白质三维重构包含百万级别粒子分类、重投影、模型重构等密集计算环节。摩尔线程GPU多核并行架构可以加速软件蛋白质重构过程，助力医学病理和结构生物学的研究。

DIGITALME数字人解决方案——摩尔线程通过视觉深度学习技术及TTS语音生成技术，构建了以单张图片、少量音频实时生成数字人的低成本、轻量化解决方案。摩尔线程数字人目前拥有表情学习、才艺模仿、给定文本自然状态讲解等功能。

随着摩尔线程对创新的不懈追求，其产品和解决方案也将不断扩展和升级，将为更多行业提供更强大的核心动力，与更广泛的合作伙伴在数字经济大潮中合作共赢。

关于摩尔线程：

摩尔线程智能科技（北京）有限责任公司是一家以GPU芯片设计为主的集成电路高科技公司，专注于研发设计全功能GPU芯片及相关产品，能够为中国科技生态合作伙伴提供强大的计算加速能力。公司成立于2020年10月，致力于创新面向元计算应用的新一代GPU，构建融合视觉计算、3D图形计算、科学计算及人工智能计算的综合计算平台，建立基于云原生GPU计算的生态系统，助力驱动数字经济发展。更多信息，请浏览官网https://www.mthreads.com/。

元计算驱动无限创新，摩尔线程重磅发布以MUSA为核心的软硬件技术方案 | 摩尔线程

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元计算驱动无限创新，摩尔线程重磅发布以MUSA为核心的软硬件技术方案 2022年11月3日 2022年11月3日，北京——摩尔线程2022秋季发布会今日在北京中关村国家自主创新示范区成功举办。发布会上，摩尔线程推出全新多功能GPU芯片“春晓”、基于MUSA架构打造的业内首款国潮显卡MTT S80和面向服务器应用的MTT S3000，以及元计算一体机MCCX。这是时隔7个月后，摩尔线程多功能GPU产品迭代创新实现的又一次跨越。不只是硬件，摩尔线程还围绕MUSA发布了系列GPU软件栈与应用工具，包括MUSA开发者套件、云原生sGPU技术及元宇宙平台MTVERSE等，旨在构建从底层芯片到上层开发和应用的整体解决方案，实现摩尔线程多功能GPU软硬件一体化创新模式的全面升维。发布会现场，摩尔线程还演示了40多个基于其多功能GPU的丰富应用，覆盖PC游戏、AI、数字人、数字孪生、物理仿真、8K多媒体显示、云游戏、云桌面、数字办公等场景，AOC、戴尔、飞利浦、骨伽、清华同方、浪潮、长城、海尔等合作伙伴为应用展示提供了设备支持，充分展示了摩尔线程强大的产品应用和生态聚合力。 MUSA不只是架构，而是一个生态 GPU是一项系统性工程，涉及硬件架构、驱动开发、软件生态、销售应用等，研发壁垒高，产业链长。当前的GPU生态，历经几十年的更迭，变得庞大且复杂。一颗GPU要完成从研发到市场的商业化应用，既离不开软硬件方面的持续投入，也离不开生态的有力支持。今年3月，摩尔线程正式发布第一颗多功能GPU芯片“苏堤”，目前已获得众多市场和生态的认可。摩尔线程PES完美体验系统联盟合作伙伴数量不断增长，覆盖CPU、操作系统、OEM厂商、软件服务厂商、云服务厂商以及系统软件开发商。基于“苏堤”芯片，摩尔线程联合OEM合作伙伴成功推出了多款个人电脑、工作站和数据中心服务器产品，应用在日常办公、数字孪生、人工智能训练和推理等业务场景；同时，携手云服务厂商为不同行业用户提供GPU云计算能力，为摩尔线程GPU在众多行业的应用落地铺平了道路。中国移动云能力中心已经与摩尔线程签署了战略合作备忘录，围绕云计算、云应用和加速计算等领域开展广泛合作；中国电信研究院将与摩尔线程围绕智能算力、科技研发、应用场景等，共同探索元宇宙新型基础设施及本土化生态，推动在关键业务场景中元宇宙技术落地应用。摩尔线程创始人兼CEO张建中在现场表达了对所有合作伙伴和用户的感谢，并进一步表示：“GPU创业是一个长期事业，充满了挑战，我们深知生态的重要性。摩尔线程多功能GPU基于先进MUSA架构，持续构建完备的软件栈及应用生态，旨在为开放生态系统创造友好的支持和体验。我们只有与生态伙伴、行业用户凝聚在一起，才能将摩尔线程的算力真正发挥出来，为元宇宙和数字经济提供核心动力。” “春晓”芯片及首款国潮游戏显卡MTT S80 保持光速前进的节奏，摩尔线程正式发布第二颗多功能GPU芯片“春晓”，集成220亿个晶体管，内置MUSA架构通用计算核心以及张量计算核心，可以支持FP32、FP16和INT8等计算精度。相较于之前发布的“苏堤”芯片，“春晓”内置的四大计算引擎全面升级，带来了显著的性能提升：图形渲染能力方面平均提升3倍；编码能力提升4倍，解码能力提升2倍；；AI计算加速平均提升4倍，物理仿真计算性能提升2.5倍。同时，引入了新技术支持窄带高清，节约带宽30%以上。全新发布的摩尔线程MTT S80基于“春晓”GPU芯片打造，也是首款面向游戏玩家打造的国潮显卡。其拥有的4096个可编程MUSA核心，在1.8GHz的主频下，能够提供14.4TFLOPS的单精度浮点算力。同时MTT S80还是业内首款配备PCIe Gen5接口的显卡产品，配合16GB GDDR6大容量高速显存，再辅以8K超高清与1080P 360Hz高刷新率显示输出能力，能为游戏玩家带来极致游戏视觉和操作体验。 MTT S80的成功推出使得摩尔线程成为国内率先支持Windows环境和DirectX图形接口的GPU公司。其强大的3D图形渲染能力将能够在Windows DirectX游戏中，为用户带来4K分辨率下的流畅操作体验。目前，MTT S80的Windows驱动已经内置了MUSA DirectX Driver模块，并已完成对《暗黑破坏神3》、《英雄联盟》和《穿越火线》等数十款主流游戏的适配。发布会现场，摩尔线程实机演示了MTT S80带来的流畅游戏运行效果。目前，摩尔线程正在与Unreal和Unity等游戏引擎开发商以及腾讯游戏、网易游戏、西山居、完美世界、360游戏（排名不分先后）等国内顶尖游戏开发商展开深度合作，以便对游戏引擎和游戏产品提供更好更快的支持，让玩家能够获得持续更新的3A级游戏体验。未来，摩尔线程将持续更新Windows驱动及MUSA DirectX版本，实现更多游戏的兼容与性能优化。摩尔线程现场宣布，MTT S80显卡已经完成首批生产与备货，将于2022年11月11日在京东电商平台开启限量销售。全新多功能服务器GPU产品MTT S3000 全新发布的MTT S3000基于摩尔线程MUSA架构，同时也是第一款基于“春晓”的多功能服务器GPU产品。摩尔线程MTT S3000的多样算力，借助覆盖图形渲染、视频处理、深度学习的完整MUSA软件栈，可为AI推理和训练、云游戏、云渲染、视频云、数字孪生、数字内容创作等场景提供通用智能算力支持，旨在为数据中心、智算中心和元计算中心的建设构建坚实算力基础，助力元宇宙中多元应用创新和落地。 MTT S3000包含了4096个MUSA流处理核心及128个专用张量计算核心，晶体管规模达到220亿，运行频率为1.9GHz，显存位宽256bit；搭配32GB GDDR6显存，带宽为448GB/s；支持FP32、FP16、INT8等多种计算精度，其中FP32算力可达15.2TFLOPS。摩尔线程MTT S3000及其配套软硬件产品，实现从算法模型到应用部署的全流程覆盖，能够为AI用户提供友好丰富的一揽子解决方案。通过MUSA计算平台的加持，在深度学习训练方面，MTT S3000兼具易用性、扩展性和兼容性等多维优势。在深度学习推理方面，MTT S3000则支持视觉、语音、自然语音理解及多模态等多个领域主流AI模型。同时，借助摩尔线程开发的CUDA ON MUSA兼容方案，用户可以将CUDA上开发的代码无缝迁移到MTT S3000。摩尔线程还对MUSA软件栈进行了深度性能优化，推出自研AI推理引擎TensorX。生态协作对于AI应用的推进至关重要。目前，MTT S3000兼容PyTorch、TensorFlow、百度飞桨（PaddlePaddle）、计图（Jittor）等多种主流深度学习框架，并实现了对Transformer、CNN、RNN等数十类AI模型的加速。摩尔线程还宣布了与百度飞桨（PaddlePaddle）、潞晨科技、计图（Jittor）、OpenMMLab和智源研究院（排名不分先后）开展战略合作，携手繁荣AI生态。加速GPU应用开发，提供丰富软件栈与工具软件生态是推动GPU计算普及的关键，以MUSA架构为核心，摩尔线程发布了完备的MUSA软件栈，以服务广大的开发者和终端用户。MUSA软件栈包括图形渲染、多媒体、人工智能、物理仿真、通用计算等功能模块，将涵盖从底层驱动到GPU加速库，再到为不同行业定制的应用领域开发套件，致力于满足各种行业场景下的应用开发需求。 ▼ MUSA开发套件：包括MUSA通用计算驱动、MUSA编译器、AI算子库、通用计算库、性能分析工具等。通过MUSA开发套件，广大MUSA开发者可以基于摩尔线程多功能GPU，在桌面PC、工作站、企业数据中心、云平台和分布式计算机集群等多种平台上开发、优化和部署各种应用程序。 ▼ CUDA ON MUSA：摩尔线程专为使用CUDA语言的用户开发了一套CUDA ON MUSA的兼容方案，通过编译与运行两步就可以让CUDA源码运行在摩尔线程MUSA架构GPU上。 ▼ MUSA用户软件：面向广大用户，提供多层次的系列软件，包括：不同系统平台的驱动、PES等平台软件系列; 基于MUSA适配并深度优化的AI框架、AI算子库、通用计算库、优化工具、容器化部署运行时库、弹性切分调度等；以及数字人、MT OCR、MT Smart Stream等云计算及应用软件系列。为了使开发者更方便获取摩尔线程系列软件栈、应用解决方案及技术支持，摩尔线程开发者网站（https://developer.mthreads.com/）正式上线，该网站将是MUSA软件产品发布、下载站点，同时也是MUSA技术交流社区，摩尔线程将围绕MUSA平台构建开放的应用及开发者生态，推动GPU生态繁荣发展。云原生GPU，加速智能云应用 GPU是当前数据中心需要的关键算力，云原生技术应用在云计算、云桌面、云游戏等领域也越来越普遍。为此，摩尔线程发布一系列基于摩尔线程创新性MT Mesh 2.0的GPU云原生方案。 MT Mesh 2.0可以根据云端中心应用负载，自动化分配GPU计算和显存资源，实现GPU算力弹性伸缩，既可以将一张GPU随意切分给多个容器或虚机，也可以支持一个容器或者虚机调度多个GPU。 ▼ 弹性容器化GPU (sGPU)：基于Kubernetes生态，使用MT Mesh 2.0实现灵活和有效调配容器化GPU资源。 ▼ 弹性虚拟化GPU(vGPU)：使用MT Mesh 2.0，率先于行业开创了资源弹性切分技术，无需重启即可动态调配和修改GPU虚拟化资源，实现算力按需调用、动态伸缩、用完释放；引入全新的“时空切分”特性，支持硬件虚拟化（SR-IOV），安全物理分割，最高支持32路虚拟化，支持Windows云桌面GPU虚拟化，以及统信和麒麟操作系统GPU直通。 ▼ 安卓容器云加速技术ACX：使用GPU安卓容器透传技术和渲染编码一体化技术，可以加速安卓云手机解决方案，减少应用延迟，增加并发路数。通过原生支持OpenGL ES、OpenGL渲染框架，和ETC/ETC2等安卓游戏材质压缩算法硬件加速，可以提供更佳的安卓云游戏渲染效果和兼容特性。云桌面与云游戏是GPU在云端的重要应用场景，摩尔线程已经与众多云桌面生态伙伴合作，提供高性价比的云桌面解决方案，服务于广大的教育、办公、金融、地理信息等行业用户。在云游戏领域，摩尔线程与腾讯先锋联合打造领先的安卓云游戏解决方案，与蔚领时代共同打造卓越的PC云游戏解决方案，致力于为广大游戏爱好者带来高画质、流畅的云游戏体验。元宇宙平台MTVERSE，构建元宇宙全场景应用方案此次发布会上，摩尔线程还发布了专为元宇宙应用构建的MTVERSE元宇宙平台及众多软硬件产品，包括基于MTT S3000打造的MCCX元计算一体机等。 MTVERSE以摩尔线程MUSA GPU集群为算力底座，为用户提供了计算基础架构服务，包括大数据、AI训练与推理、图形渲染和物理仿真三大平台，提供从硬件集群、软件基础架构到SDK工具链的全栈式解决方案，涵盖元宇宙中的人、场景和内容等多个核心要素。而上层的海量SDK工具则能帮助开发者和应用程序方便的调用这些能力，实现数字人、文献理解、语音识别、视觉识别、自然语义理解、对话交互、物理仿真、AIGC内容生成等一系列功能，进一步简化应用和解决方案的开发周期和难度。 ▼ AlphaCore物理仿真引擎升级：新增2款全新物理仿真产品，包括液体交互仿真工具Flood Dynamics和气象及云动力学仿真Storm System；并全面提升了气体流体仿真工具CatalystFX、布料毛发制作工具VeraFiber的效果与效率。摩尔线程宣布与云原生渲染引擎RaysEngine深度集成，实现数字孪生实时3D渲染与物理仿真，制作更加逼真的数字化场景。 ▼ DIGITALME数字人解决方案升级：构建完整的数字人生产线，包括“女娲”数字人生成器、“画皮”表情驱动引擎、“随影”数字人动作驱动引擎，以及“随答”数字人对话系统。 ▼ AIGC内容生成器马良：支持中英双语的图文生成、图文编辑，为用户提供零门槛的AIGC创作平台，助力科技和人文的融合。摩尔线程还与云南艺术学院展开合作，为艺术家提供端到端的“算力与算法”解决方案，联合组建“设计学院AI艺术创作实验室”，并开设马良课程，培养设计专业的学生，助力艺术创作。 ▼ MCCX元计算一体机：旨在提供强大且易用的元计算算力，针对AI、渲染、编解码等元算力应用场景，MCCX设计了合理的系统架构和资源配比，为用户提供高性价比的元算力硬件解决方案；并采用软硬件一体化交付的方式，预置完整的基础软件栈，开发环境、AI和渲染框架，支持一键式的应用部署和升级，实现元计算算力的开箱即用。关于摩尔线程摩尔线程智能科技（北京）有限责任公司是一家以GPU芯片设计为主的集成电路高科技公司，专注于研发设计全功能GPU芯片及相关产品，能够为中国科技生态合作伙伴提供强大的计算加速能力。公司成立于2020年10月，致力于创新面向元计算应用的新一代GPU，构建融合视觉计算、3D图形计算、科学计算及人工智能计算的综合计算平台，建立基于云原生GPU计算的生态系统，助力驱动数字经济发展。欲了解更多信息，请您访问摩尔线程官方网站https://www.mthreads.com/ 最新资讯浏览更多声明：摩尔线程MUSA/MUSIFY未受影响 2024年3月6日摩尔线程获评“北京市数字经济标杆企业” 2024年3月5日同时更新！摩尔线程发布 v250.60 游戏显卡驱动和 v2.5.0 Ubuntu 驱动 2024年2月22日社区开发者社区摩卡玩家合作 PES 联盟购买京东旗舰店关注我们官方旗舰店用户许可协议合规声明法律声明隐私政策

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摩尔线程发布MUSA统一系统架构及系列GPU产品 - 知乎

摩尔线程发布MUSA统一系统架构及系列GPU产品 - 知乎切换模式写文章登录/注册摩尔线程发布MUSA统一系统架构及系列GPU产品DeepTech深科技科技话题下的优秀答主“我来钱塘拓湖绿，大堤士女争昌丰。六桥横绝天汉上，北山始与南屏通。”这是苏东坡任杭州刺史时，主持疏浚西湖、修筑堤岸期间留下的诗句。该堤岸名为苏堤，现已是西湖十景之首。每年春风拂过，苏堤岸杨柳飘飘、桃花灼灼，景色使人醉。今年3月30日，摩尔线程举办了以“元动力创无限”为主题的春季发布会。会上，创始人兼CEO张建中发布了统一系统架构及一系列相关产品。其中，第一代摩尔线程多功能GPU芯片“苏堤”正式亮相并成为全场焦点，它与西湖苏堤同名，又在春季首次推出，饱含设计者的美好寓意。“元计算”这一概念由摩尔线程首次提出，意指以图形计算和AI计算为基，为覆盖元宇宙在内的下一代互联网应用的算力平台提供底层算力支撑，不断推动物理世界数字化和数字世界物理化的发展。对此，张建中认为：“元计算时代已然开启，多功能CPU是元计算的算力基础设施，也是我们创新的原点。摩尔线程致力于面向元计算应用的新一代GPU创新，构建融合视觉计算、3D图形计算、科学计算及人工智能计算的通用计算平台，建立基于云原生GPU计算的生态系统，助力数字经济发展。此次系列新品的发布，是公司发展的重大里程碑，更是我们研发实力、生态凝聚力和创新执行力的集中体现。”MUSA统一系统架构及系列新品发布，赋能数字经济发展本次发布会上发布的产品主要包括MUSA统一系统架构、第一代多功能GPU芯片“苏堤”、桌面级显卡MTT S60、图形渲染和计算卡 MTT S2000、GPU物理引擎AlphaCore、DIGITALME数字人解决方案以及多个元计算应用解决方案。MUSA（Moore Threads Unified System Architecture）统一系统架构主要面向计算、图形、多媒体和人工智能产品线，包括统一编程模型、软件运行库、驱动程序框架、指令集架构和芯片架构。该架构能增强应用的可移植性，使后者可在云端和边缘等计算平台上同时运行，符合减少软件开发者重复劳动、释放不同引擎核心能力的设计初衷。“苏堤”基于MUSA架构研发，是第一代摩尔线程多功能GPU芯片。该芯片内置现代图形渲染引擎（Graphics Engine）、智能多媒体引擎（Smart Media Engine）、AI计算加速引擎（AI Engine）、科学计算与物理仿真（Physics Engine）等四大引擎以及3D图形计算核芯、AI训练与推理计算核芯、高性能并行计算等核芯，能够满足数字经济包括云边端在内的多元算力需求。在图像渲染上，苏堤芯片能够实现高精度纹理渲染、全局照明与环境光、景深渲染等多种效果。在适配和运行上，苏堤芯片搭载主流编程接口，符合MUSA/CUDA、Vulkan、DirectX、OpenGL Runtime等，已经完成对国产主流CPU和操作系统的适配，并且可以支持多个编辑器平台，给开发者提供通用的开发环境。在实时交互上，此芯片支持如视频云、直播、8K 游戏等智能多媒体运用，在发布会现场《英雄联盟》电子竞技对战上取得良好效果。MTT S60显卡是摩尔线程第一代多功能智能显卡，主要面向PC和工作站，具有优秀的图形和视频处理能力、强大的AI算法支持及特殊的绿色能效技术，可以在数字办公、图形渲染、智能制造CAD/CAE、建筑设计BIM、人工智能应用等领域发挥超强的算力支持。它采用12nm制程，包含2048个MUSA核心，搭载8GB显存，像素填充率为192G Pixel/s，单精度浮点运算最高可达6TFLOPS。首先，该显卡有丰富的图形API接口，支持DirectX、Vulkan、OpenGL和OpenGL ES，满足各类高图形负载应用对2D和3D图形渲染的需求，有利于设计者高效完成各类设计工作。其次，MTT S60显卡在硬件视频编解码能力上领先同类产品，不仅支持主流的H.264、H.265编码格式与AV1视频格式的硬件编码，有利于企业降低视频处理成本，还支持AV1、H.264、H.265等诸多格式的硬件解码，降低CPU负载，在提升用户体验的同时增强计算机整体效能。同时，它能够加速DBNet、CRNN、Yolo、Restnet50/101等AI模型推理计算，还支持多种复杂人工智能场景。并且，由于MTT S60显卡支持多种纹理压缩算法，所以它也能为高清视频处理、复杂模型设计以及大AI模型等高负载应用提供更高水平的显存带宽利用率。此外，该显卡支持英特尔、AMD、龙芯、飞腾等主流CPU平台和Windows、麒麟等操作系统。目前，摩尔线程已与联想、清华同方、浪潮等多家合作伙伴展开进一步合作。MTT S2000是摩尔线程打造的第一款数据中心级多功能GPU产品，其采用12nm制程，使用4096个MUSA核心，搭载32GB显存，单精度算力最高可达到12TFlops。该产品内置音视频编解码、渲染、人工智能加速和并行计算等硬件模块，能够提供包括图形图像渲染、视频云处理、AI和科学计算在内一系列功能。MTT S2000以行业标准SR-IOV（单根I/O 虚拟化）技术为基础，能够使每个物理GPU上容纳多个虚拟化用户远程工作，凭借MUSA架构中的MT Mesh 1.0 GPU虚拟化技术，它还能在虚拟化架构中获得更高的效率。此外，摩尔线程给该系列产品提供了专门优化硬件架构的统一编程模型、运行库和驱动等软件工具，开发者可充分借助MTT S2000的硬件资源和算力去完成应用的适配和移植。目前，MTT S2000支持x86和ARM架构CPU。作为摩尔线程独立研发的下一代多平台GPU物理仿真系统，AlphaCore能够实现对物理世界中复杂固体、柔性体等超高精度的物理仿真处理，并在运算模拟的基础之上，使毛发、布料和数字角色软体肌肉组织达到电影般真实的物理交互效果。同时，凭借超强的材料力学模块，AlphaCore可实现丰富的材料交互动态效果。此外，该引擎还提供了多平台兼容版本，可以在最大程度上兼容游戏引擎和设计软件，覆盖影视后期制作、游戏、建筑等应用场景。DIGITALME数字人解决方案是摩尔线程在视觉深度学习技术和TTS语音生成技术的基础上构建的数字人轻量化和低成本兼具的解决方案。目前，用单张照片和少量音频就能使数字人完成表情学习、才艺模仿和给定文本自然状态的讲解。如今，摩尔线程正与多家合作伙伴联手打造各行各业元计算的解决方案。在数字农业方面，摩尔线程与埃舍尔科技联合打造数字化示范种植基地，借助数字化种植，实现品种溯源，保障品种质量，推动农村数字化不断发展。在数字城市方面，摩尔线程与光线云、51World联手，探索数字孪生和云原生渲染，以超强的GPU通用计算、高清视频处理等能力，助推政府和企业的数字化转型。在数字能源方面，摩尔线程与国网电商科技共建智能计算芯片联合应用研究实验室，推进“电力行业人工智能”及“工业元宇宙电力场景”应用。在数字生命方面，摩尔线程GPU多核并行架构能够加速软件蛋白质的重构，帮助医学病理和结构生物学研究更进一步。团队引领，技术加持，摩尔线程创立18个月即实现国产GPU的商品化突破摩尔线程智能科技（北京）有限责任公司于2020年10月成立，是一家以GPU芯片设计为主的集成电路高科技公司，将研发原创自主知识产权的GPU芯片和提供超强的计算加速能力作为主要发展方向。创始人兼CEO张建中曾担任NVIDIA全球副总裁、中国区总经理，他在GPU行业深耕多年，带领NVIDIA在中国建立了完整的GPU生态系统。公司不仅拥有超过700名来自全球范围内顶尖的GPU人才，还吸引到了微软、英特尔等科技公司核心团队的加盟。公司仅成立100天，就获得了深创投、红杉资本中国基金等多家机构数十亿元的融资，所筹资金主要用于技术研发、市场拓展和后续产品的开发。去年11月，摩尔线程宣布成功研制首颗国产全功能GPU。公司成立18个月后，就推出了可以上市销售的国产全功能的系列产品。摩尔线程方表示：“摩尔线程是国内唯一一支真正世界级的、能够覆盖GPU研发设计、生产制造、市场销售、服务支持等完整架构的成熟团队。目前，公司已与数百个生态伙伴建立合作关系，共同推进国产GPU应用软件的联合开发、性能优化和应用创新。”编辑于 2022-04-01 09:28系统架构系统线程赞同 2添加评论分享喜欢收藏申请

芭蕉属_百度百科

百度百科网页新闻贴吧知道网盘图片视频地图文库资讯采购百科百度首页登录注册进入词条全站搜索帮助首页秒懂百科特色百科知识专题加入百科百科团队权威合作下载百科APP个人中心收藏查看我的收藏0有用+10芭蕉属播报讨论上传视频芭蕉目芭蕉科下属植物本词条由“科普中国”科学百科词条编写与应用工作项目审核。芭蕉属（Musa L.），是芭蕉目芭蕉科下的一属植物，有30种及很多变种，主产东半球的热带地区，中国约10种，分布于西南部至台湾。芭蕉属代表植物有香蕉M. nana Lour. [M. acuminata Colla（AA A）]、大蕉M. sapientum L. （M. acuminata Colla x M. balbisiana Colla），为广东、台湾重要果品之一，此外，福建、广西、云南等省亦有栽培；红蕉M. coccinea Andr.间有栽培供观用。（概述图来源： [1]）中文名芭蕉属拉丁学名Musa L.界植物界门被子植物门纲木兰纲 [5]目姜目科芭蕉科属芭蕉属分布区域主产亚洲东南部属拼音名bajiaoshu中国植物志16(2):6目录1形态特征2分布范围3主要价值4下级分类5检索表形态特征播报编辑芭蕉属(5张)多年生丛生草本，具根茎，多次结实。假茎全由叶鞘紧密层层重叠而组成，基部不膨大或稍膨大，但绝不十分膨大呈坛状；真茎在开花前短小。叶大型，叶片长圆形，叶柄伸长，且在下部增大成一抱茎的叶鞘。花序直立，下垂或半下垂，但不直接生于假茎上密集如球穗状；苞片扁平或具槽，芽时旋转或多少覆瓦状排列，绿、褐、红或暗紫色，但绝不为黄色，通常脱落，每一苞片内有花1或2列，下部苞片内的花在功能上为雌花，但偶有两性花上部苞片内的花为雄花，但有时在栽培或半栽培的类型中，其各苞片上的花均为不孕。合生花被片管状，先端具5 (3+2) 齿，二侧齿先端具钩、角或其它附属物或无任何附属物；离生花被片与合生花被片对生；雄蕊5；子房下位，3室。浆果伸长，肉质，有多数种子，但在单性结果类型中为例外；种子近球形、双凸镜形或形状不规则。染色体数目：X=10或11，稀7或9。 [2]分布范围播报编辑芭蕉属(6张)约40种，主产亚洲东南部。我国连栽培种在内有10种，浙江栽培3种，温州栽培2种，其中1种逸生，此外据记载台湾还有M. formosana (Wall.) Hayata 及 M. insularimontana Hayata 2种，因标本未见，未收入本志。 [2] [6]主要价值播报编辑芭蕉属植物为热带亚热带地区一类重要的植物资源。蕉麻（马尼拉麻）的假茎纤维可供制作耐海水浸泡的绳缆。栽培的香蕉（或大蕉）为热带、亚热带地区的著名水果之一，亦可用以代粮，主要制成蕉干（或蕉粉）以供食用。芭蕉干或芭蕉粉的营养相当丰富（据粗分析：淀粉74%，蛋白质3.7-4.2%，脂肪0.51%，水分1.2-1.9%），其中蛋白质含量相当高，芭蕉淀粉特别易于消化，含维生素甲、乙、丙都丰富，完全适于作人类的主食。同时芭蕉作为一种作物，还有很多优点：产量高（亩产平均5,000斤，去皮后净肉重 3,000斤，可得淀粉1,000斤；国外亦有报道其亩产量比马铃薯还要高），可连续收获 4-8年，省劳力，全年收获，忙闲均等，加工容易，可种在山地，不占水田，病虫害少，水旱灾影响不大。 [2]从综合利用的角度来讲，芭蕉果皮可喂猪，雄花可作蔬菜，芭蕉干心除可喂猪、酿酒外，尚可制粉；假茎纤维可作麻并可织布（称蕉葛），也可烧灰制碱，叶可包物或提取蜡粉，可以说全身无废物。野生种类的芭蕉可作遗传育种上的原始材料，其中有些种类花苞红色鲜艳，可供观赏，惟其果实及花、嫩心、根头常有毒，不能食用。 [2]下级分类播报编辑小果野蕉 Musa acuminata，野蕉 Musa balbisiana，芭蕉 Musa basjoo，红蕉 Musa coccinea，台湾芭蕉 Musa formosana (Wall.) Hayata，岛山芭蕉 Musa insularimontana Hayata，阿宽蕉 Musa itinerans，勒加卜蕉 Musa nagensium Prain，香蕉 Musa nana，阿希蕉 Musa rubra，大蕉 Musa sapientum，蕉麻 Musa textilis Née， [3]树头芭蕉 Musa wilsonii。检索表播报编辑1苞片通常多少具槽，多少灰白色，具光泽或无光泽，芽时旋转或多少覆瓦状，凋落时通常明显外卷；种子通常背腹压扁，偶有近球形，有时双凸镜状，或为不规则棱形，光滑或具疣，有与种脐相对生的明显或不明显的一个小突起；染色体数目：X=11。(2)1苞片扁平，质地坚硬，外面具光泽，稀或不为灰白色，芽时明显覆瓦状，凋落时不或稍外卷；染色体数目：x=10。(10)2花序至少在基部是直立的，因而浆果在发育时不倒向，但仍是指向序轴的顶端；每一苞片内少花，排成一列；苞片颜色鲜艳，常为红色；假茎高在3米以下[红芭蕉组 Sect. Rbodochlamys (Bak.) Cheesm. ]。离生花被片比合生花被片短很多；序轴被褐色微柔毛。阿希蕉2花序初时下垂或半下垂，浆果倒向果轴基部发育；每一苞片内多花，排成2列；苞片通常暗色，绿、褐或暗紫色；假茎通常高3米以上（芭蕉组sect. Musa）。(3)3栽培种：果实通常无种子，可食。(4)3野生种；果实充满种子，不堪食。(5)4雄花苞片不脱落。香蕉4雄花苞片脱落。大蕉5叶鞘上部及叶背均被蜡粉。(6)5叶鞘上部及叶背无蜡粉或微被蜡粉。(7)6浆果具长柄，柄长在2厘米以上；雄花暗紫红或紫红色；种子扁球形。野蕉6浆果具短柄，柄长不及1厘米；雄花白色，上部带橙黄色；种子不规则多棱形。小果野蕉7根茎伸长，长在1 米以上。(8)7根茎短，丛生；雄花苞片覆瓦状。(9)8浆果具长柄。阿宽蕉8浆果近无柄。芭蕉9浆果具长柄，柄长3.5-4.5厘米。树头芭蕉9浆果具短柄，柄长不及1厘米。小果野蕉10种子近球形或多少背腹压扁，光滑，具条纹，具疣，或具不规则的棱，有与种脐相对生的明显或不明显的一个小突起，此突起内部为外胚乳小室（南芭蕉组 sect. Australimusa Cheesm.）。果串疏松，成熟时黄色；雄花长为宽的2-3倍；合生花被片外侧二裂片兜状或具角；浆果不开裂；叶翼紧密闭合，边缘膜质，有细而密的皱褶。蕉麻10种子圆柱状、桶状或陀螺状，外面明显有一横线或沟纹，在此横线上方具疣、小突起或各种花纹，横线下方通常光滑，内面在横线上方有一个十分发达的外胚乳室，此室在成熟种子中是空的（美芭蕉组 sect. Callimusa Cheesm.) 。假茎高约1米；苞片深红色；花被乳黄色，离生花被片与合生花被片几等长；序轴无毛 [3]红蕉新手上路成长任务编辑入门编辑规则本人编辑我有疑问内容质疑在线客服官方贴吧意见反馈投诉建议举报不良信息未通过词条申诉投诉侵权信息封禁查询与解封©2024 Baidu 使用百度前必读 | 百科协议 | 隐私政策 | 百度百科合作平台 | 京ICP证030173号京公网安备110000020000

The banana (Musa acuminata) genome and the evolution of monocotyledonous plants | Nature

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The banana (Musa acuminata) genome and the evolution of monocotyledonous plants

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Published: 11 July 2012

The banana (Musa acuminata) genome and the evolution of monocotyledonous plants

Angélique D’Hont1 na1, France Denoeud2,3,4 na1, Jean-Marc Aury2, Franc-Christophe Baurens1, Françoise Carreel1,5, Olivier Garsmeur1, Benjamin Noel2, Stéphanie Bocs1, Gaëtan Droc1, Mathieu Rouard6, Corinne Da Silva2, Kamel Jabbari2,3,4, Céline Cardi1, Julie Poulain2, Marlène Souquet1, Karine Labadie2, Cyril Jourda1, Juliette Lengellé1, Marguerite Rodier-Goud1, Adriana Alberti2, Maria Bernard2, Margot Correa2, Saravanaraj Ayyampalayam7, Michael R. Mckain7, Jim Leebens-Mack7, Diane Burgess8, Mike Freeling8, Didier Mbéguié-A-Mbéguié9, Matthieu Chabannes5, Thomas Wicker10, Olivier Panaud11, Jose Barbosa11, Eva Hribova12, Pat Heslop-Harrison13, Rémy Habas5, Ronan Rivallan1, Philippe Francois1, Claire Poiron1, Andrzej Kilian14, Dheema Burthia1, Christophe Jenny1, Frédéric Bakry1, Spencer Brown15, Valentin Guignon1,6, Gert Kema16, Miguel Dita19, Cees Waalwijk16, Steeve Joseph1, Anne Dievart1, Olivier Jaillon2,3,4, Julie Leclercq1, Xavier Argout1, Eric Lyons17, Ana Almeida8, Mouna Jeridi1, Jaroslav Dolezel12, Nicolas Roux6, Ange-Marie Risterucci1, Jean Weissenbach2,3,4, Manuel Ruiz1, Jean-Christophe Glaszmann1, Francis Quétier18, Nabila Yahiaoui1 & …Patrick Wincker2,3,4 Show authors

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AbstractBananas (Musa spp.), including dessert and cooking types, are giant perennial monocotyledonous herbs of the order Zingiberales, a sister group to the well-studied Poales, which include cereals. Bananas are vital for food security in many tropical and subtropical countries and the most popular fruit in industrialized countries1. The Musa domestication process started some 7,000 years ago in Southeast Asia. It involved hybridizations between diverse species and subspecies, fostered by human migrations2, and selection of diploid and triploid seedless, parthenocarpic hybrids thereafter widely dispersed by vegetative propagation. Half of the current production relies on somaclones derived from a single triploid genotype (Cavendish)1. Pests and diseases have gradually become adapted, representing an imminent danger for global banana production3,4. Here we describe the draft sequence of the 523-megabase genome of a Musa acuminata doubled-haploid genotype, providing a crucial stepping-stone for genetic improvement of banana. We detected three rounds of whole-genome duplications in the Musa lineage, independently of those previously described in the Poales lineage and the one we detected in the Arecales lineage. This first monocotyledon high-continuity whole-genome sequence reported outside Poales represents an essential bridge for comparative genome analysis in plants. As such, it clarifies commelinid-monocotyledon phylogenetic relationships, reveals Poaceae-specific features and has led to the discovery of conserved non-coding sequences predating monocotyledon–eudicotyledon divergence.

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MainBanana cultivars mainly involve M. acuminata (A genome) and Musa balbisiana (B genome) and are sometimes diploid but generally triploid5,6. We sequenced the genome of DH-Pahang, a doubled-haploid M. acuminata genotype (2n = 22), of the subspecies malaccensis that contributed one of the three acuminata genomes of Cavendish7. A total of 27.5 million Roche/454 single reads and 2.1 million Sanger reads were produced, representing 20.5× coverage of the 523-megabase (Mb) DH-Pahang genome size, as estimated by flow cytometry. In addition, 50× of Illumina data were used to correct sequence errors. The assembly consisted of 24,425 contigs and 7,513 scaffolds with a total length of 472.2 Mb, which represented 90% of the estimated DH-Pahang genome size. Ninety per cent of the assembly was in 647 scaffolds, and the N50 (the scaffold size above which 50% of the total length of the sequence assembly can be found) was 1.3 Mb (Supplementary Text and Supplementary Tables 1–3). We anchored 70% of the assembly (332 Mb) along the 11 Musa linkage groups of the Pahang genetic map. This corresponded to 258 scaffolds and included 98.0% of the scaffolds larger than 1 Mb and 92% of the annotated genes (Supplementary Text, Supplementary Table 4 and Supplementary Fig. 1).We identified 36,542 protein-coding gene models in the Musa genome (Supplementary Tables 1 and 5). A total of 235 microRNAs from 37 families were identified, including only one of the eight microRNA gene (MIR) families found so far solely in Poaceae8 (Supplementary Tables 6 and 7).Viral sequences related to the banana streak virus (BSV) dsDNA plant pararetrovirus were found to be integrated in the Pahang genome, with 24 loci spanning 10 chromosomes (Supplementary Text and Supplementary Fig. 2). They belonged to a badnavirus phylogenetic group that differed from the endogenous BSV species (eBSV) found in M. balbisiana9 and most of them formed a new subgroup (Supplementary Fig. 3). Importantly, all of the integrations were highly reorganized and fragmented and thus did not seem to be capable of forming free infectious viral particles, contrary to the eBSV described in M. balbisiana10.Transposable elements account for almost half of the Musa sequence (Supplementary Text and Supplementary Tables 1 and 8–10). Long terminal repeat retrotransposons represent the largest part, with Copia elements being much more abundant than Gypsy elements (25.7–11.6%) (Supplementary Fig. 4). No major recent wave of long terminal repeat retrotransposon insertions appears to have occurred in the Musa lineage. Fewer than 1% of the long terminal repeat retrotransposons are complete and their median date of insertion is around 4 Myr ago, corresponding to the half-life of this type of transposable element11 (Supplementary Fig. 5). Long interspersed elements (LINEs) represent 5.5% of the genome. The banana genome is exceptional in the composition of its class 2 element population, which represents only about 1.3% of the genome. The only superfamilies identified were hAT, followed by Harbinger and Mutator. Only the first family was significantly represented and had non-autonomous deletion derivatives. The superfamilies CACTA and Mariner, which have been found in high copy numbers in all angiosperm genomes studied so far, are absent from the banana genome. Gene-rich regions are mostly located on distal parts of chromosomes, as observed in other plant genomes (Fig. 1 and Supplementary Fig. 1). There is, however, a particularly sharp transition between gene-rich and transposable-element-rich regions. This observation is confirmed by the pattern observed after genomic in situ hybridization, which shows that transposable elements are typically concentrated around centromeres in Musa12 (Supplementary Fig. 6). The asymmetric transposable element distributions along the chromosomes indicated that chromosomes 1 and 2 are acrocentric in DH-Pahang (Fig. 1). Long terminal repeat retrotransposons are particularly abundant in centromeric and pericentromeric chromosome regions. Their accumulation in these regions, particularly for the oldest ones, suggests that they are preferentially eliminated from gene-rich regions13 (Supplementary Fig. 5). Remarkably, typical short tandem centromeric repeats were not found in Musa. However, one long interspersed element (named Nanica) identified in the unassembled reads was localized by fluorescence in situ hybridization in the centromeric region of all Musa chromosomes (Supplementary Fig. 7 and Supplementary Table 10).Figure 1:

Chromosomal distribution of the main

M. acuminata

genome features.

Distribution of genes and transposable elements (left) and paralogous relationships between the 11 chromosomes indicated with 12 distinct colours corresponding to the 12 Musa α/β ancestral blocks (right). LINEs, long interspersed elements.

PowerPoint slide

Full size imageWhole-genome duplications (WGDs) have played a major role in angiosperm genome evolution14; the first evidence of a WGD event in the Musa lineage was reported by Lescot et al.15. We uncovered a complex pattern of paralogous relationships between the 11 Musa chromosomes (Supplementary Text and Supplementary Fig. 8). Most paralogous gene clusters shared relationships with three other clusters, suggesting that two WGDs (denoted as α and β) occurred (Supplementary Fig. 9). Based on Ks and synteny relationships, duplicated gene clusters were tentatively assembled into 12 Musa ancestral blocks representing the ancestral genome before the α/β duplications (Figs 1 and 2 and Supplementary Figs 10–12). The duplicated segments included in the Musa ancestral blocks cover 222 Mb (67% of the anchored assembly) and contain 26,829 genes (80% of the anchored genes) (Supplementary Table 11). The Ks distribution among pairs of paralogous gene clusters dated the two WGDs at a similar period around 65 Myr ago (Supplementary Fig. 13), consistent with the WGDs that occurred in many different plant lineages near the Cretaceous–Tertiary boundary14 (Fig. 3). Additional paralogous relationships between the 12 Musa ancestral blocks displaying higher Ks values suggested that an additional, more ancient duplication event (denoted as γ) occurred around 100 Myr ago (Fig. 3 and Supplementary Figs 10, 11, 13 and 14).Figure 2:

Whole-genome duplication events.

a, Paralogous relationships between chromosome segments from Musa α/β ancestral blocks 2 (red) and 8 (green). The 12 Musa α/β ancestral blocks are shown in different colours on the circle. b, Orthologous relationships of Musa ancestral blocks 2 and 8 with rice ancestral blocks ρ2, ρ5 and σ6. We did not observe a one-to-one relationship between, for instance, Musa α/β ancestral block 2 and one ρ ancestral block, which suggests that the γ and σ duplications are two separate events. c, Representation of the deduced WGD event.

PowerPoint slide

Full size imageFigure 3:

Timing of whole-genome duplications relative to speciation events within representative monocotyledons and eudicotyledons.

Boxes indicate WGD events. Green boxes indicate WGD events analysed in this paper. All nodes have 100% bootstrap support in a maximum likelihood analysis. Branch lengths (synonymous substitution rate) are indicated. The timing of the β WGD event relative to the Musaceae/Zingiberaceae split remains to be clarified.

PowerPoint slide

Full size imageIn the grass lineage, it is well established that one WGD (denoted as ρ) occurred around 50–70 Myr ago, after Poales separated from other monocotyledon orders16,17. Evidence was reported on an additional WGD (denoted as σ) earlier in the monocotyledon lineage, but after its divergence from the eudicotyledons18. Our comparison of the Musa ancestral blocks with the Poaceae ρ and σ ancestral blocks as defined by Tang et al.18 revealed that genes from segments of different ρ blocks (corresponding to one σ block) have orthologous relationships with the same Musa regions, showing that the σ Poaceae event is not shared with Musa. Reciprocally, genes from Musa α/β paralogous segments have orthologous relationships with the same ρ and σ regions, showing that the earliest duplication (γ) we identified in the Musa lineage is not shared with Poaceae (Fig. 2 and Supplementary Fig. 15).Independent phylogenomic analyses performed on 3,553 gene families, including genes mapped to syntenic ancestral blocks, generated further evidence (98.7–77.6% of the gene trees, Supplementary Text) that the three rounds of palaeopolyploidization identified in the Musa genome and the two previously reported in the Poaceae lineage occurred independently after the Poales and Zingiberales divergence estimated at 109–123 Myr ago19 (Fig. 3 and Supplementary Fig. 16).Resolution of the Zingiberales relationship relative to Poales and Arecales (palms) has been problematic (see, for example, Givnish et al.20), but our analysis of 93 single-copy nuclear genes suggested that the palms are more closely related to Zingiberales (including Musa) than to Poales (Fig. 3, Supplementary Text and Supplementary Fig. 17). Phylogenomic and synteny analyses indicated that the palms do not, however, share any of the Poales or Zingiberales WGDs discussed here (Supplementary Figs 17 and 18). Moreover, our Ks analyses of date-palm gene models21 indicated that the palm genome had its own WGD event (Supplementary Fig. 19).Most (65.4%) of the genes included in the Musa α/β ancestral blocks are singletons and only 10% are retained in four copies, in agreement with the loss of most gene-duplicated copies after WGD22. The most retained gene ontology categories corresponded to genes involved in transcription regulation (transcription factor activity), signal transduction including small GTPase-mediated signal transduction and protein kinases, and translational elongation (Supplementary Text and Supplementary Tables 12–14). This might be explained by the gene balance hypothesis23, which suggests that genes involved in multiproteic complexes or regulatory genes are dosage sensitive and thus are more prone to be co-retained or co-lost after WGD24. With 3,155 genes, the number of Musa transcription factors identified is among the highest of all sequenced plant genomes (Supplementary Table 15 and 16).Comparison of Musa, rice, sorghum, Brachypodium, date palm (Phoenix dactylifera) and Arabidopsis proteomes revealed 7,674 gene clusters in common to all six species, thus representing ancestral gene families (Fig. 4). Interestingly, many specific clusters (2,809 in our setting) proved specific to Poaceae, suggesting a high level of gene divergence and diversification within the grass lineage. Specific Musa clusters (759) were enriched in genes encoding transcription factors (for example, Myb and AP2/ERF families), defence-related proteins, enzymes of cell-wall biosynthesis and enzymes of secondary metabolism (Supplementary Table 17).Figure 4: Six-way Venn diagram showing the distribution of shared gene families (sequence clusters) among M. acuminata, P. dactylifera, Arabidopsis thaliana, Oryza sativa, Sorghum bicolor and Brachypodium distachyon genomes.Numbers of clusters are provided in the intersections. The total number of sequences for each species is provided under the species name (total number of sequences/total number of clustered sequences).

PowerPoint slide

Full size imageWe compared the distribution of GC3 content (G or C in the third codon position) in Musa coding sequences with those of rice, ginger (Zingiber officinale) and date palm because this distribution was shown to be bimodal in Poaceae and unimodal in all analysed eudicotyledons25. In Musa, a GC-rich peak was apparent but less distinct from the GC-poor one (Supplementary Text, Supplementary Figs 20–23 and Supplementary Table 18), which confirms preliminary evidence that placed Musa in an intermediate position15. This feature was shared with ginger (Zingiberales) and contrasts with the unimodal GC distribution of date-palm coding sequences (Supplementary Fig. 21).Plant conserved non-coding sequences (CNSs)—a type of phylogenetic footprint—are enriched in known transcription factors or other cis-acting binding sites, and are usually clustered around regulatory genes, supporting their functionality26. Starting with a collection of 16,978 CNSs conserved in Poaceae, we used the Musa genome to identify the 116 most deeply conserved regulatory binding sequences in the commelinid monocotyledon lineage (Supplementary Text, Supplementary Tables 19 and 20, and Supplementary Fig. 24). Deeply conserved CNSs in commelinids were frequently found located 5′ to genes encoding transcription factors, and were significantly enriched in WRKY motifs (Supplementary Table 21). After WGD, genes associated with deeply conserved CNSs were found to be retained as duplicates more often than genes with less deeply conserved CNSs (Supplementary Table 22). The banana genome also served as a stepping-stone to finding CNSs conserved beyond monocotyledons, including 18 CNSs that were found in this study to be conserved in the expected syntenic position in eudicotyledons as well (Supplementary Table 23). This evolutionary distance is not unusual for vertebrate CNSs (detectable after more than 400 million years of divergence)27 but it surpasses the findings of previous plant whole-genome surveys26. Plant deeply conserved CNSs are therefore rare but do exist, and are short compared with those of animals27, and must be at least as old as monocotyledon–eudicotyledon divergence (more than 130 million years of divergence).The reference Musa genome sequence represents a major advance in the quest to unravel the complex genetics of this vital crop, whose breeding is particularly challenging. Having access to the entire Musa gene repertoire is a key to identifying genes responsible for important agronomic characters, such as fruit quality and pest resistance. Bananas are exported green and then ripened by application of ethylene. RNA-Seq analysis indicated strong transcriptional reprogramming in mature green banana fruits after ethylenic treatment (Supplementary Text, Supplementary Tables 24–26 and Supplementary Fig. 25). Transcription factors were particularly involved with 597 differentially regulated genes. Various modifications confirmed the biochemistry of the banana ripening process28, such as highly upregulated genes encoding cell-wall modifying enzymes, three downregulated starch synthase genes and one upregulated β-amylase gene. Two WGD-derived paralogous vacuolar invertase genes involved in sucrose conversion displayed opposite expression profiles, suggesting subfunctionalization and possible contribution to the soluble sugar balance in ripening bananas (Supplementary Fig. 26). The race against pathogen evolution is particularly critical in clonally propagated crops such as banana. Up to 50 pesticide treatments a year are required in large plantations against black leaf streak disease, a recent pandemy caused by Mycosphaerella fijiensis3. Moreover, outbreaks of a new race of the devastating Panama disease fungus (Fusarium oxysporum f. sp. cubense) are spreading in Asia4. Among defence-related genes, those encoding nucleotide-binding site leucine-rich repeat proteins were found to be little represented in the Musa sequence (89 genes) (Supplementary Table 27). RNA-Seq analysis showed that receptor-like kinase genes were upregulated in a partially resistant interaction with M. fijiensis (Supplementary Text, Supplementary Table 28 and Supplementary Fig. 27). Interestingly, direct links between basal plant immunity triggered by receptor-like kinase proteins and quantitative trait loci for partial resistance have been recently established in several plant species (see, for example, Poland et al.29). In addition, we showed that DH-Pahang is highly resistant to the new broad-range Fusarium oxysporum race 4 (Supplementary Text and Supplementary Fig. 28), thus conferring additional specific value to the DH-Pahang sequence.The Musa genome sequence reported here bridges a large gap in genome evolution studies. As such, it sheds new light on the monocotyledon lineage. Several Poaceae-specific characteristics could be highlighted, boosting prospects for analysing the emergence of this very successful family. The Musa genome also enabled identification of deeply conserved CNS within commelinid monocotyledons and between monocotyledons and eudicotyledons, representing an invaluable resource for detecting novel motifs with a gene regulation function. We detected three rounds of polyploidization in the Musa lineage, which were followed by gene loss and chromosome rearrangements, resulting in little synteny conservation between lineages (Supplementary Figs 29 and 30) and over-retention of some gene classes, thus providing ample opportunities for independent diversification. In particular, transcription factor families are strikingly expanded in Musa compared with other plant genomes and probably contribute to specific aspects of banana development.The Musa genome sequence is therefore an important advance towards securing food supplies from new generations of Musa crops, and provides an invaluable stepping-stone for plant gene and genome evolution studies.Methods SummarySanger (ABI 3730xl sequencers) and Roche/454 (GSFLX pyrosequencing platform) reads were assembled with Newbler. Scaffolds were anchored to Pahang linkage groups using 652 markers (SSR and DArT). Protein-coding gene model prediction on the repeat-masked sequence was done with the GAZE30 computational framework by combining ab initio gene predictions, protein similarity, existing banana and monocotyledon transcript information and banana RNA-Seq data. A reference library of Musa transposable elements was built based on sequence similarity at the protein and nucleic acid levels and on searches for transposable-element structural signatures. The library was used with the REPET package (http://urgi.versailles.inra.fr/Tools/REPET) to screen the Musa assembly and quantify repeats.RNA-Seq differential gene expression analysis was performed using Illumina GAIIx 76 bases reads that were mapped to the DH-Pahang sequence using SOAP2 (http://soap.genomics.org.cn/).Online MethodsPlant material and DNA preparationDoubled-haploid Pahang (DH-Pahang, ITC1511) was obtained from wild M. acuminata subspecies malaccensis accession ‘Pahang’ through anther culture and spontaneous chromosome doubling31. Genome sizes were estimated by flow cytometry according to Marie and Brown32. High molecular weight DNA was prepared from the youngest fully expanded leaf of DH-Pahang as described in Piffanelli et al.33 with minor modifications (Supplementary Text).Genome sequencingThe genome was sequenced using a Whole Genome Shotgun strategy combining Sanger, Roche/454 GSFLX and Illumina GAIIx technologies. Sanger sequencing was performed with the ABI 3730xl on 10-kilobase (kb) inserts and on two BAC libraries generated with the HindIII and BamHI restriction enzymes resulting in 2.0 million 10-kb fragment-ends and about 90,500 BAC-ends. A total of 27.5 million reads were obtained using Roche/454 GSFLX.Genome assembly and automatic error corrections with Solexa/Illumina readsAll reads were assembled with Newbler version MapAsmResearch-03/15/2010. From the initial 29,620,875 reads, 87.8% were assembled. We obtained 24,425 contigs that were linked into 7,513 scaffolds. The contig N50 (the contig size above which 50% of the total length of the sequence assembly is included) was 43.1 kb, and the scaffold N50 was 1.3 Mb. The cumulative scaffold size was 472.2 Mb, about 10% smaller than the estimated genome size of 523 Mb. Sequence quality of scaffolds from the Newbler assembly was improved as described previously34, by automatic error corrections with Solexa/Illumina reads (50-fold genome coverage), which have a different bias in error type compared with 454 reads. To validate the assembly, we built a unigene set corresponding to 15,017 isotigs that were obtained from the assembly with Newbler (version MapAsmResearch-03/15/2010) of Roche/454 GSFLX reads from six different complementary DNA (cDNA) libraries (829,587 reads, Supplementary Text). The unigenes were aligned with the assembly using the BLAT algorithm35 with default parameters, and the best match was kept for each unigene. The assembly covers a very large proportion of the euchromatin of the M. acuminata genome, as 99% of the set of 15,017 unigenes was recovered in the DH-Pahang genome assembly.Construction of the Pahang genetic map and sequence anchoringA genetic map was specifically developed for scaffold anchoring and orientation. A total of 2,454 single sequence repeats (SSR) markers and 1,008 polymorphic diversity array technology (DArT) markers were analysed including 1,411 new SSRs defined on sequence contigs and scaffolds. The map used for anchoring was built with 589 SSR and 63 DArT markers that were genotyped on 180 individuals of the Pahang self progeny. Data were analysed using JoinMap 4 (Plant Research International). The 652 markers anchored 258 scaffolds along the 11 linkage groups of the genetic map. Orientation of scaffolds was possible when two or more separated genetic markers were present on the same scaffold. All these data were used to generate 11 banana pseudo-chromosomes with 100Ns inserted between neighbouring scaffolds (Supplementary Fig. 1 and Supplementary Table 4).Gene predictionThe following resources were integrated to automatically build Musa acuminata gene models using GAZE30: ab initio gene predictions from Geneid36, SNAP37 and FGENESH38; Genewise39 alignments of the UniProt40 database; Est2genome41 alignments of full-length cDNAs from six tissue samples of DH-Pahang and a collection of 6,888,879 monocotyledon messenger RNAs from the EMBL database and finally Gmorse models42 derived from RNA-Seq reads (Supplementary Text). MicroRNAs were predicted based on comparison using the Plant MicroRNA Database (http://bioinformatics.cau.edu.cn/PMRD/).Identification of integrated pararetrovirus sequencesViral integrants in the DH-Pahang genome were detected with a BLASTN analysis using either full-length BSV sequences or a 540-base-pair fragment of the RT/RNase H region of the badnaviruses genome (Supplementary Text).Identification, classification and distribution of Musa transposable elementsMusa transposable elements were identified based on sequence similarity at the protein and nucleic-acid levels using BLASTP and TBLASTN43 and by de novo identification based on transposable-element structural signatures. Repeats from 1,832,094 remaining unassembled reads were characterized with a BLASTN ‘walking’ approach44. The obtained reference Musa transposable-element library was used with REPET45 to screen the assembly and quantify repeats (Supplementary Text). Insertion dates of full-length long terminal repeat retrotransposons were determined as described in Ma et al.46 with a substitution rate of 9 × 10−9 per site per year, which is twofold higher than that determined for Musa genes by Lescot et al.15.Identification of Musa WGDs and comparative genome analysesFor the identification of Musa WGD, an all-against-all comparison of Musa proteins was done using the GenomeQuest BLAST package (LASSAP47) and retaining ten best hits for each gene. Clusters of paralogues composed of at least 20 genes with a maximal distance of 40 genes between syntenic genes were built with an in-house perl script, using a single linkage clustering with a Euclidian distance based on the gene index order in each chromosome. These clusters were refined using Synmap (http://synteny.cnr.berkeley.edu/CoGe/SynMap.pl) with the BLASTZ algorithm, an average distance expected between syntenic genes of 10, a maximum distance between two matches of 30, a minimum number of aligned gene pairs of 10 and a quota-align ratio of 3 to 3 (Supplementary Text).For comparative genome analyses, orthologous gene-pairs were identified using predicted proteomes of M. acuminata, O. sativa (IRGPS/RAP, build 4), Vitis vinifera (http://www.genoscope.cns.fr/externe/Download/Projets/Projet_ML/data/12X/annotation/) and Phoenix dactylifera (draft sequence version 3, http://qatar-weill.cornell.edu/research/datepalmGenome/download.html). Alignments were performed using BLASTP (e value 1 × 10−5) and retaining best hits. Syntenic clusters of genes were built using a single linkage clustering with a Euclidian distance. Dot-plots were performed using an in-house perl program allowing the painting of paralogous and orthologous gene clusters. Circle diagrams were made with Circos48.To calculate the number of synonymous substitutions per site (Ks), ClustalW49 alignments of paralogous and orthologous protein sequences were used to guide nucleic coding sequence alignments with PAL2NAL50. Ks values were calculated using the Yang–Nielson method implemented in PAML51.Phylogenomic analysisTo infer the timing of genome duplication events relative to speciation events, all annotated Musa genes were sorted based on best BLASTP hit into the gene family clusters circumscribed by Jiao et al.52 and the PlantTribes database53 (http://fgp.bio.psu.edu/tribedb/), including sequenced eudicotyledons and monocotyledons, along with transcriptome assemblies for other non-grass monocotyledons (Supplementary Text). Gene family clusters were queried for Sorghum18 and Musa orthologues mapping to syntenic blocks, and maximum likelihood gene trees were estimated for these gene families using the GTR+GAMMA model of molecular evolution in RAxML54. The estimation of divergence times was performed on maximum likelihood trees based on concatenated MAFFT55 alignments for 93 gene families that included only one gene from each of the sequenced genomes (Supplementary Text).Comparative analysis of gene familiesThe Musa proteome was globally compared with O. sativa (RGAP version 6.0), S. bicolor (JGI version 1.4), B. distachyon (JGI version 1.0), P. dactylifera (draft sequence version 3, http://qatar-weill.cornell.edu/research/datepalmGenome/download.html) and A. thaliana (TAIR version 9) proteomes filtered of transposable elements and alternative splicing. An all-against-all comparison was performed using BLASTP (1 × 10−10) followed by clustering with OrthoMCL56 (inflation 1.5). Analysis of species-specific sets was made with a Fisher’s exact test (P < 0.0001) on InterPro (version 28) domains. For analyses of specific gene families, the 36,542 Musa protein sequences were inserted in the plant proteome clustering of the GreenPhyl database57. Transcription factor families were mostly retrieved based on InterPro domains, using the IPR2genomes tool in GreenphylDB57 (Supplementary Text). Kinases and nucleotide-binding site proteins were retrieved using hidden markov models (hmmsearch version 3) to search for corresponding Pfam domains (Supplementary Text).Identification of CNSsPan-grass CNSs conserved between rice, sorghum and Brachypodium were prepared using an automated pipeline58. The obtained 16,978 CNSs were used to query Musa using BLATSN (e value < 0.001) following a manual or a semi-automated procedure depending on CNS size (Supplementary Text and Supplementary Fig. 24). The resulting set of CNSs was extensively analysed using GEvo59 (http://synteny.cnr.berkeley.edu/CoGe/GEvo.pl) and the MSU Rice Genome Browser60 (http://rice.plantbiology.msu.edu/cgi-bin/gbrowse/rice/) to remove false positives (Supplementary Table 19). Adding rice and sorghum homeologues, Brachypodium and maize orthologues and Arabidopsis ‘best hit orthologues’ to GEvo panels enabled the identification of 18 CNSs conserved deeply throughout the plant kingdom.Transcriptome sequencingFor RNA-Seq analyses (Supplementary Text), cDNA libraries were sequenced using 76-base length read chemistry in a single-flow cell on the Illumina GA IIx. Reads were mapped against the automatic annotated transcripts with SOAPaligner/Soap2 (2.20, http://soap.genomics.org.cn/) and only the unique mapped reads were kept. RNA-seq data were statistically analysed with the R packages baySeq version 1.6.0 (ref. 61) and DESeq version 1.5.6 (ref. 62).

Accession codes

Primary accessions

GenBank/EMBL/DDBJ

CAIC01000001–CAIC01024424

HE806462–HE813974

HE813975–HE813985

Data deposits

The final assembly and annotation are deposited in DDBJ/EMBL/ GenBank under accession numbers CAIC01000001–CAIC01024424 (contigs), HE806462–HE813974 (scaffolds) and HE813975–HE813985 (chromosomes). Genome sequence and annotation can be obtained and viewed at http://banana-genome.cirad.fr.

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Download referencesAcknowledgementsThis work was mainly supported by French National Research Agency, Commissariat à l’Energie Atomique and Centre de coopération Internationale en Recherche Agronomique pour le Développement. The Generation Challenge program supported DArT genotyping, and Stichting Het Groene Woudt part of BAC-end sequencing. We thank M. Teixeira Souza for authorizing early access to BAC-End sequences, L. Baudouin and T. Hardcastle for their help with the Bayseq analysis, O. Inizan, T. Flutre and F. Choulet for their help in transposable-element mapping. We thank the SouthGreen Bioinformatics Platform (http://southgreen.cirad.fr) for providing us with computational resources. We thank D. Manley for his help with the English in this paper.Author informationAuthor notesAngélique D’Hont and France Denoeud: These authors contributed equally to this work.Authors and Affiliations Centre de coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), UMR AGAP, F-34398 Montpellier, France , Angélique D’Hont, Franc-Christophe Baurens, Françoise Carreel, Olivier Garsmeur, Stéphanie Bocs, Gaëtan Droc, Céline Cardi, Marlène Souquet, Cyril Jourda, Juliette Lengellé, Marguerite Rodier-Goud, Ronan Rivallan, Philippe Francois, Claire Poiron, Dheema Burthia, Christophe Jenny, Frédéric Bakry, Valentin Guignon, Steeve Joseph, Anne Dievart, Julie Leclercq, Xavier Argout, Mouna Jeridi, Ange-Marie Risterucci, Manuel Ruiz, Jean-Christophe Glaszmann & Nabila Yahiaoui Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, 2 rue Gaston Crémieux, BP5706, 91057 Evry, France , France Denoeud, Jean-Marc Aury, Benjamin Noel, Corinne Da Silva, Kamel Jabbari, Julie Poulain, Karine Labadie, Adriana Alberti, Maria Bernard, Margot Correa, Olivier Jaillon, Jean Weissenbach & Patrick Wincker Centre National de Recherche Scientifique (CNRS), UMR 8030, CP5706, Evry, France , France Denoeud, Kamel Jabbari, Olivier Jaillon, Jean Weissenbach & Patrick Wincker Université d’Evry, UMR 8030, CP5706, Evry, France , France Denoeud, Kamel Jabbari, Olivier Jaillon, Jean Weissenbach & Patrick Wincker CIRAD, UMR BGPI, Campus international de Baillarguet, F-34398 Montpellier, France , Françoise Carreel, Matthieu Chabannes & Rémy Habas Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier Cedex 5, France , Mathieu Rouard, Valentin Guignon & Nicolas RouxDepartment of Plant Biology, University of Georgia, Athens, 30602, Georgia, USASaravanaraj Ayyampalayam, Michael R. Mckain & Jim Leebens-MackDepartment of Plant and Microbial Biology, University of California, Berkeley, 94720, California, USADiane Burgess, Mike Freeling & Ana Almeida CIRAD, UMR QUALISUD Station de Neufchâteau, Sainte-Marie, 97130 Capesterre-Belle-Eau, France , Didier Mbéguié-A-Mbéguié Institute of Plant Biology, University of Zurich, CH-8008 Zurich, Switzerland , Thomas Wicker Laboratoire Génome et Développement des Plantes, UMR 5096 CNRS-UPVD, 66000 Perpignan, France , Olivier Panaud & Jose Barbosa Centre of the Region Hana for Biotechnological and Agricultural Research, Institute of Experimental Botany, Sokolovska 6, CZ-77200 Olomouc, Czech Republic , Eva Hribova & Jaroslav DolezelDepartment of Biology, University of Leicester, Leicester LE1 7RH, UK, Pat Heslop-Harrison Diversity Arrays Technology, Yarralumla, Australian Capital Territory 2600, Australia , Andrzej Kilian Institut des Sciences du Végétal, CNRS UPR 2355 et FRC3115, 91198 Gif-sur-Yvette, France , Spencer Brown University of Wageningen, Plant Research International, 6700 AA Wageningen. Netherlands , Gert Kema & Cees WaalwijkDepartment of Plant Sciences, University of Arizona, Tucson, Arizona, USAEric LyonsDépartement de Biologie, Université d’Evry Val d’Essonne, Evry, France, Francis Quétier Brazilian Agricultural Research Corporation (EMBRAPA), Embrapa Cassava & Fruits, Cruz das Almas, 44380-000, Salvador, Bahia, Brazil., Miguel DitaAuthorsAngélique D’HontView author publicationsYou can also search for this author in

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PubMed Google ScholarContributionsJ.M.A., F.C.B., F.C., O.G., B.N. and S.B. contributed equally to this work. J.P., K.L., J.M.A. and M.B. performed sequencing and assembly. S.Br. performed genome size evaluation. F.C.B., N.R. and G.K. built or gave access to BAC libraries or BAC-end sequences. B.N., S.Bo., F.D., M.Co., J.Len., C.D.S., G.D., M.Ro., N.Y., F.C.B. and V.G. performed protein coding gene annotation. F.C., F.C.B., C.C., M.S., G.D., R.H., R.R., P.F., A.K., C.Je., F.B., S.J., M.R.G. and A.M.R. performed plant material development, ploidy analysis, DNA extraction, markers development, genotyping, genetic mapping, anchoring. K.J. performed gene GC content analyses. S.Bo., O.G., T.W., E.H., P.H.H., J.B., M.R.G., D.Burt., A.D.H., M.J., C.P., J.D., O.P., J.Len., G.D. and N.Y. performed transposable-element analysis. O.G., F.D., A.D.H., J.M.A., G.D., F.C.B., E.L., S.Bo. and O.J. performed WGD analyses based on synteny conservation. J.L.M., S.A., M.R.M., A.D.H., O.G. performed phylogenomic analyses of WGD. N.Y., M.Ro., J.Len., S.Bo., C.Jo., A.D., F.D., M.Ru. and A.Alm. performed gene family analyses. J.Lec., X.A., G.D. and S.Bo. performed transfer RNA and microRNA analyses. F.C.B. and M.Ch. performed endogenous virus analyses. D.Burg. and M.F. performed CNS analyses. N.Y., C.Jo., C.D.S., A.Alb., F.C., D.M.M., M.D., C.W., G.K., M.S., performed RNA extraction, phenotyping and/or transcriptomic analyses. A.D.H., N.Y., O.G., F.C., F.C.B., F.D., J.M.A., J.C.G., P.W., S.Bo., F.Q. and J.W. wrote or revised the paper. A.D.H., N.Y. and P.W. conceived and coordinated the whole project.Corresponding authorsCorrespondence to

Angélique D’Hont or Patrick Wincker.Ethics declarations

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Supplementary informationSupplementary InformationThis file contains Supplementary Text and Data 1-18 (see Contents for details), Supplementary References, Supplementary Figures 1-30, Supplementary Tables 1-19, 21-23, 27 (see separate zipped for file for Supplementary Tables 20, 24-26 and 28). (PDF 9831 kb)Supplementary TablesThis zipped file contains Supplementary Tables 20, 24-26 and 28. (ZIP 1200 kb)PowerPoint slidesPowerPoint slide for Fig. 1PowerPoint slide for Fig. 2PowerPoint slide for Fig. 3PowerPoint slide for Fig. 4Rights and permissions

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Reprints and permissionsAbout this articleCite this articleD’Hont, A., Denoeud, F., Aury, JM. et al. The banana (Musa acuminata) genome and the evolution of monocotyledonous plants.

Nature 488, 213–217 (2012). https://doi.org/10.1038/nature11241Download citationReceived: 10 February 2012Accepted: 18 May 2012Published: 11 July 2012Issue Date: 09 August 2012DOI: https://doi.org/10.1038/nature11241Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard

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Editorial SummaryBanana genome-sequence analysisBananas (Musa spp.) are a staple food and a major source of income in many tropical and subtropical countries. This paper reports the sequencing and analysis of the banana genome. This is the first non-grass monocotyledon to have its genome sequenced, providing an important bridge for comparative genome analysis in plants. Global banana production is under threat from increasingly well-adapted pests and diseases, so the availability of the genome sequence is an important resource for future crop development and improvement.show all

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小果野蕉_百度百科

_百度百科网页新闻贴吧知道网盘图片视频地图文库资讯采购百科百度首页登录注册进入词条全站搜索帮助首页秒懂百科特色百科知识专题加入百科百科团队权威合作下载百科APP个人中心小果野蕉播报讨论上传视频芭蕉科芭蕉属植物收藏查看我的收藏0有用+10小果野蕉（学名：Musa acuminata Colla）是芭蕉科、芭蕉属的多年生草本植物。 [4]假茎高约480厘米，油绿色，带黑斑，被蜡粉；叶长圆形，上面绿色，被蜡粉，下面黄绿色，被蜡粉或无，上面中脉绿色，下面白黄色；叶柄被蜡粉，叶翼张开；花被片先端三裂，中裂片两侧有小裂片，两侧裂片先端具钩；果序被白色刚毛，浆果圆柱形，内弯，绿或黄绿色，被白色刚毛，具有五棱。 [2]小果野蕉分布于中国云南东南部至西部及广西西部，在印度北部，缅甸，泰国，越南，经马来西亚至菲律宾等国家亦有分布。适应性强，分布广，多生长于海拔1200米以下的阴湿的沟谷、沼泽、半沼泽及坡地上。 [5]小果野蕉的果实具有清热解毒、润肺滑肠的功效，主治热病烦渴、肺燥咳嗽、痔疮、便秘等症状。 [6]其嫩叶可以炒熟食用也可腌酸食用，也可采用水蒸气蒸馏法提取其芳香成分制作精油。 [7]假茎也可作为猪饲料，亚洲象还喜欢吃它的茎秆。 [8]中文名小果野蕉拉丁学名Musa acuminata Colla [3]界植物界门被子植物门纲木兰纲目姜目科芭蕉科属芭蕉属种小果野蕉命名者及年代Colla，1820目录1植物学史2形态特征3近种区别4产地生境5生长习性6主要价值植物学史播报编辑名称由来芭蕉属名Musa是为了纪念公元前63年至公元14年的罗马医生和植物学家安东尼乌斯·穆萨（Antonius Musa），种加词acuminata是一个拉丁词，意思是尖锐或渐尖（指其果实的尖端），指的是果实的尖锐顶端。 [17]栽培起源以小果野蕉的小孢子培养后加倍获得了其双单倍型植株De Pahang，并于2012年完成了全基因组测序，为研究香蕉相关的分子机理奠定了良好的基础。进一步的研究表明，小果野蕉在细胞质水平上与现代广泛栽培的栽培种巴西蕉非常接近，推测其是巴西蕉进化起源的重要供体种之一。同时，小果野蕉也被利用于杂交育种以相关机理研究。通过小果野蕉与Pisang Lily杂交，构建了其分子图谱，并发现两者减数分裂过程中染色体的相互作用异常。 [9]形态特征播报编辑假茎高约4.8米，油绿色，带黑斑，被有蜡粉。叶片长圆形，长1.9-2.3米，宽50-70厘米，基部耳形，不对称，叶面绿色，被蜡粉，叶背黄绿色，无蜡粉或被蜡粉，中脉上面绿色，下面白黄色；叶柄长约0.8米，被蜡粉，叶翼张开约0.6厘米。 [1]小果野蕉雄花合生花被片先端3裂，中裂片两侧有小裂片，二侧裂片先端具钩，钩上有毛，离生花被片长不及合生花被片之半，先端微凹，凹陷处具小尖突。果序长1.2米，总梗长达0.7米，直径4厘米，被白色刚毛。浆果圆柱形，长约9厘米，内弯，绿色或黄绿色，被白色刚毛，具5棱角，先端收缩而延成长0.6厘米的喙，基部弯，下延成长不及1厘米的柄，果内具多数种子，种子褐色，高3毫米。 [1]近种区别播报编辑小果野蕉常与同属的野蕉杂交培育食用香蕉， [16]两者在形态上较为相似，区别点在于：小果野蕉：有明显的黑色或棕色斑点，叶柄管边缘直立或展开，有翅；梗通常被毛，花梗相对较短，胚珠的每个小室有两排规则行，雄花颜色为乳白色，柱头橙色或浓黄色；苞片外部呈红色、暗紫色或黄色，内部呈粉红色、暗紫色或黄色，内部苞片颜色通常向基部褪色为黄色，披针形或狭卵形，从肩部急剧变细，苞片反折且打开后回卷。 [17]野蕉：假茎斑点非常轻微或不存在，叶柄管边缘封闭，无翅；梗无毛，花梗相对较长，胚珠的每个小室有四行不规则行，雄花粉红色且多变，柱头奶油色、淡黄色或淡粉色；苞片外部独特的棕紫色，内部明亮的深红色，内部苞片颜色通常连续至基部，宽卵形，不急剧变细，不反折，顶端钝。 [17]产地生境播报编辑小果野蕉分布于中国云南东南部至西部及广西西部，在印度北部，缅甸，泰国，越南，经马来西亚至菲律宾等国家亦有分布。小果野蕉应性强，分布广，多生于阴湿的沟谷、沼泽、半沼泽及坡地上；海拔1200米以下。 [1]生长习性播报编辑小果野芭蕉全年开花并单次结实，除进行种子繁殖外同时具有较强的克隆生长能力。小果野芭蕉往往通过种子传播实现对新生境的定居而通过根蘖繁殖实现对已进入地的占据，在林窗、砍伐迹地及刀耕火种撂荒地等光照条件好的地方甚至能迅速形成以小果野芭蕉为主的单优群落。小果野芭蕉定居后形成斑块状聚集群落可能会明显地影响和改变群落的组成、结构和演替方向。 [14]小果野蕉自由分蘖，在不同的季节可以给犬蝠提供食物。犬蝠取食小果野芭蕉时，咀嚼并吞下果肉后把种子吐出丢弃到进食地下面，被吐出的种子和未利用的果肉粘在一起形成一个团。 [12]果实被动物取食后种子随动物的粪便传播，或沿沟谷随流水传播。在热带雨林内，由于光照弱等原因，很少有小果野芭蕉存在种子被传播后在合适的条件下迅速萌发生长，在一两年内便能达到正常高度，并以根部的萌芽迅速扩大其种群数量，所以在刀耕火种轮歇地、砍伐迹地和林窗形成的初始阶段，小果野芭蕉和一些先锋植物往往最先侵入，逐渐形成以其为优势的单优群落，并在一定的时期内存在。 [13]主要价值播报编辑药用价值：小果野蕉的果实具有清热解毒、润肺滑肠的功效，主治热病烦渴、肺燥咳嗽、痔疮、便秘等症状。 [6]食用价值：小果野蕉其嫩叶可以炒熟食用也可腌酸食用。 [7]经济价值：小果野蕉是世界上栽培香蕉的亲本种之一，其假茎可作猪饲料， [10]亚洲象还喜欢吃它的茎秆。 [8]其嫩叶也可采用水蒸气蒸馏法提取其芳香成分制作精油。 [7]科研价值：小果野蕉是现代香蕉栽培种的祖先之一，在理论研究和应用中有非常重要的地位。 [9]观赏价值：小果野蕉适合在公园、风景区的路边、水岸边栽培观赏。 [11]生态价值：小果野芭蕉是热带地区最为常见的一种大型草本先锋植物。小果野芭蕉在森林更新与热带和亚热带山地的生态恢复等方面具有特殊重要的地位。 [15]新手上路成长任务编辑入门编辑规则本人编辑我有疑问内容质疑在线客服官方贴吧意见反馈投诉建议举报不良信息未通过词条申诉投诉侵权信息封禁查询与解封©2024 Baidu 使用百度前必读 | 百科协议 | 隐私政策 | 百度百科合作平台 | 京ICP证030173号京公网安备110000020000

4096核，32GB显存！摩尔线程发布全新元计算架构MUSA和GPU产品_AI&大模型_李冬梅_InfoQ精选文章

英伟达不允许模拟跑CUDA 摩尔线程：MUSA/MUSIFY未受影响_腾讯新闻

英伟达不允许模拟跑CUDA 摩尔线程：MUSA/MUSIFY未受影响

DoNews3月5日消息，近日，网络上有报道称，英伟达CUDA 11.6的EULA（最终用户许可协议）中有条款提到，“不能逆向工程、反编译或反汇编使用此SDK生成的任何结果，并在非英伟达平台上进行转译。”（You may not reverse engineer, decompile or disassemble any portion of the output generated using SDK elements for the purpose of translating such output artifacts to target a non-NVIDIA platform）」

国内GPU厂商摩尔线程通过其官方公众号澄清，摩尔线程MUSA/MUSIFY不涉及英伟达EULA相关条款，开发者可放心使用。

摩尔线程称，MUSA是摩尔线程自主研发、拥有全部知识产权、软硬一体的全功能GPU先进计算统一系统架构，与CUDA无任何依赖关系。

MUSIFY是摩尔线程面向广大MUSA开发者提供的开发工具，方便用户在MUSA计算平台上进行应用移植与开发，可以让开发者将自己的C++源代码，转换成MUSA C++源代码，再通过MUSA编译器MCC编译生成基于MUSA指令集的二进制代码，最终运行在摩尔线程全功能GPU上。

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tokenpocket官方网址是多少|musa

tokenpocket官方网址是多少|musa

如何评价摩尔线程发布基于 MUSA 统一系统架构发布的 GPU? - 知乎

摩尔线程：MUSA/MUSIFY不涉英伟达EULA相关条款，开发者可放心使用|源代码|musa|英伟达eu|musify_网易订阅

自研MUSA架构！摩尔线程发布4096核心服务器GPU，还有桌面级显卡_腾讯新闻

元计算驱动无限创新，摩尔线程重磅发布以MUSA为核心的软硬件技术方案 | 摩尔线程

摩尔线程发布MUSA统一系统架构及系列GPU产品 - 知乎

芭蕉属_百度百科

The banana (Musa acuminata) genome and the evolution of monocotyledonous plants | Nature

小果野蕉_百度百科

4096核，32GB显存！摩尔线程发布全新元计算架构MUSA和GPU产品_AI&大模型_李冬梅_InfoQ精选文章

英伟达不允许模拟跑CUDA 摩尔线程：MUSA/MUSIFY未受影响_腾讯新闻

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