RHINE IPU
新型超高速AI推理 IPU芯片 与 分布式集群架构
Technical Highlights
高达 14000~22000 Token/s 的超高速大模型推理
适配所有主流的 AI 大语言模型
极高的流水线并行处理能力 支持大量用户并发
下一代 AGI 必备基础设施
Computing Architecture Comparison
1×4096 Vector — 4096×4096 Matrix Performance Analysis
Systolic Array Animation
Page 4Global Clock / Cycles
0000
Google TPU Strategy
0
/ 11
Time ComplexityO(N)
Degree of ParallelismN2
Our Parallel Architecture
0
/ 3
Time ComplexityO(1) + O(Log2 N)
Degree of ParallelismN2
Performance Gain — ~945x Acceleration
Cycles reduced from 12287 to 13 via massive parallelization.
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VECTOR IN
+
Sum Unit 1
SUM
I/O
I/O
NORMALIZE
Norm Type
VECTOR MATRIX MULTIPLYCOMPUTE CORE
+
Sum Unit 2
ACTIVATION
Activation
VAL
×
Multiply Unit
+
Sum Unit 3
VECTOR OUT
AUX VECTOR IN
Control2 BIT
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联系我们
Contact Us
Mail: Official@RHINE.AI
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