Data Center Computers: Modern Challenges in CPU Design

Table of Contents

https://www.youtube.com/watch?v=QBu2Ae8-8LM

Data Center环境下面对于CPU设计的挑战。虽然是标题是关于CPU设计挑战,但是其实里面没有说怎么设计CPU,而是点出了问题背景。了解这些问题背景,对于分析data center环境下面的应用程序,是非常有帮助的。

数据中心机器面临4个问题:

  1. Move data: big and small 如何在内存中快速地移动数据
  2. Real-time transactions: 1000s per second 大量的实时事务,不可避免地会遇到长尾问题
  3. Isolation between programs 程序之间是通过软件进行隔离的,隔离效果并不理想
  4. Measurement underpinnings 更好的测量方式(sampling vs tracing) http://danluu.com/perf-tracing/

1 Move data: big and small

数据中心的Server好像是下面这样的,CPU L3 Cache(i7 12MB)相比RAM简直没有办法比,大量的money也放在RAM上。

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因为数据中心设计到大量的数据move, 如果我们想快速移动数据,比如16 bytes CPU cycle. 那么我们需要做到:

  1. 至少16字节的寄存器,并且每个周期会有load/store/test/branch. 并且是至少4路并行。
  2. 如果是3.2Ghz的CPU,那么吞吐必须在50GB/s. 如果加上读写那么就是100GB/s
  3. 如果write之前还需要读cache line的话,那么就需要150GB/s. 所以还需要使用non-temporary write. 最后加一个mfence.

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因为还涉及到比较短的字符串挪动,为了处理对齐情况,CPU上最好支持比如 load/store partial R1,R2, R3这样的指令可以快速挪动16字节以内的变长字节。

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如果整个pipeline都能保持100GB/s的话,那么L3 Cache/RAM之间的持续带宽必须在400GB/s.

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2 Real-time transactions: 1000s per second

如何更好地控制长尾延迟:锁持有时间,调度延迟, 以及共享资源之间相互影响(这个和后面资源隔离性有关系)

Modern challenges in CPU design

  • A single transaction can touch thousands of servers in parallel
  • The slowest parallel path dominates
  • Tail latency is the enemy
    • Must control lock-holding times
    • Must control scheduler delays
    • Must control interference via shared resources

3 Isolation between programs

影响主要来自于软件,但是硬件上需要提供机制来进行隔离,比如CPU Cache可以根据cpu thread来进行隔离

Many Sources of Interference

  • Most interference comes from software
  • But a bit from the hardware underpinnings
  • In a shared apartment building, most interference comes from jerky neighbors
  • But thin walls and bad kitchen venting can be the hardware underpinnings

Isolation between programs

  • Good fences make good neighbors
  • We need better hardware support for program isolation in shared memory systems

Modern challenges in CPU design

  • Isolating programs from each other on a shared server is hard
  • As an industry, we do it poorly
    • Shared CPU scheduling
    • Shared caches
    • Shared network links
    • Shared disks
  • More hardware support needed
  • More innovation needed

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4 Measurement underpinnings

Samples只能看到大体状况,而Traces则可以提供更多的细节。 http://danluu.com/perf-tracing/

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作者介绍了根据trace发现的一个因为CPU throttle造成disk server经常出现高延迟的问题,而这种东西使用sampling是发现不了的。然后作者搞了一个Sites' corollary: 如果一个问题可以解释为软件复杂性的,那就不要解释成为愚蠢。

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对于CPU设计上要提供low overhead的tracing机制,这样可以zoom in发现更加细微的问题。

Modern challenges in CPU design

  • Need low-overhead tools to observe the dynamics of performance anomalies
    • Transaction IDs
    • RPC trees
    • Timestamped transaction begin/end
  • Traces
    • CPU kernel+user, RPC, lock, thread traces
    • Disk, network, power-consumption