DKbench runs the benchmark suite single-threaded and multi-threaded (2 threads in this comparison as we use 2x vCPU instances) and calculates a scalability percentage. The benchmark obviously uses highly parallelizable workloads (if that's not what you are running, you'd have to rely more on the single-thread benchmarking). In the following graph 100% scalability means that if you run 2 parallel threads, they will both run at 100% speed compared to how they would run in isolation. For systems where each vCPU is 1 core (e.g. all ARM systems), or for "shared" CPU systems where each vCPU is a thread among a shared pool, you should expect scalability near 100% - what is running on one vCPU should not affect the other when it comes to CPU-only workloads.
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，更多细节参见搜狗输入法
但在风光背后，从芯片到云，从大模型到应用，一系列技术、产业与社会的变化正在发生，某种约束已若隐若现：Scaling Law（缩放定律）和通用GPU多年来的统治地位受到挑战，云厂商巨额Capex（资本开支）的验证时间窗口收窄，“定制化”和“个性化”等分布式需求愈发吃重，让集中式的迅猛增长有落潮之虞。
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infrequent, this eliminates the binding stack walk entirely from the