字節跳動豆包UltraMem架構將大模型推理成本降低83%
字節跳動豆包大模型團隊今日宣佈，成功研發出全新稀疏模型架構UltraMem，該架構有效解決了MoE（混合專家）模型推理時的高額訪存問題，推理速度較MoE提升2-6倍，推理成本最高可降低83%。這一突破性進展爲大模型的高效推理開闢了新路徑。UltraMem架構在保證模型效果的前提下，成功解決了MoE架構推理時的訪存瓶頸。實驗結果表明，在參數和激活條件相同的情況下，UltraMem不僅模型效果優於MoE，更將推理速度提升了2-6倍。此外，在常見batch size規模下，UltraMem的訪存成本幾乎與同計算量的Dense
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