面向大模型訓練,騰訊發佈超強算力集羣,性能提升三倍!
就在剛剛,$騰訊控股(00700.HK)$發佈了號稱國內性能最強的大模型計算集羣。
據騰訊微信公衆號4月14日消息,騰訊雲正式發佈面向大模型訓練的新一代HCC(High-Performance Computing Cluster)高性能計算集羣。
該集羣採用騰訊雲星星海自研服務器,搭載英偉達最新代次H800 GPU,服務器之間採用業界最高的3.2T超高互聯帶寬,爲大模型訓練、自動駕駛、科學計算等提供高性能、高帶寬和低延遲的集羣算力。
據騰訊介紹,實測顯示,新一代集羣整體性能比過去提升了3倍,是國內性能最強的大模型計算集羣。
早在去年10月,騰訊訓練框架AngelPTM,完成了首個萬億參數大模型訓練——混元NLP大模型訓練。在同等數據集下,將訓練時間由 50 天縮短到 11 天。如果基於新一代集羣,訓練時間將進一步縮短至 4 天。
針對大模型場景,星星海自研服務器採用 6U 超高密度設計,相較行業可支持的上架密度提高 30%;利用並行計算理念,通過 CPU 和 GPU 節點的一體化設計,將單點算力性能提升至更高。
除此以外,H800 GPU也是新集羣的一大看點。公開資料顯示,H800爲英偉達旗下最先進的芯片之一,對人工智能研發極爲重要,其算力超過旗艦芯片A100三倍,這也是國內首次發佈搭載H800的大模型產品。
網絡層面,騰訊發佈自研的星脈網絡能提供3.2T通信帶寬,爲業內最高數據。
騰訊表示,搭載同樣的GPU卡,3.2T星脈網絡相較前代網絡,能讓集羣整體算力提升20%,使得超大算力集羣仍然能保持通信開銷比和吞吐性能。並提供單集羣高達十萬卡級別的組網規模,支持更大規模的大模型訓練及推理。
存儲層面,幾千臺計算節點同時讀取一批數據集,需要儘可能縮短加載時長。騰訊雲自研的文件存儲、對象存儲架構,具備TB級吞吐能力和千萬級IOPS,滿足大模型訓練的大數據量存儲要求。
新一代集羣還集成了騰訊雲自研的 TACO 訓練加速引擎,對網絡協議、通信策略、AI 框架、模型編譯進行大量系統級優化,大幅節約訓練調優和算力成本。
另外,騰訊自研芯片已經量產,包括用於AI推理的紫霄芯片。它採用自研存算架構和自研加速模塊,可以提供高達3倍的計算加速性能和超過45%的整體成本節省。
在上月召開的電話會議上,騰訊方面表示,未來將投入大量資源並建立自己的基礎模型,並將其整合進公司的所有業務中。不過騰訊表示,將做對的事,不會倉促行事。
騰訊還說,AIGC可以用來提升騰訊旗下旗艦產品的用戶體驗。未來可能每一個用戶都會有人工智能助理,如果效果好,有可能將生成式AI納入微信和QQ。
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