Accurate emulation of CPU performance Tomasz Buchert 1 Lucas Nussbaum - - PowerPoint PPT Presentation

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Oct 03, 2023 227 likes •471 views

Accurate emulation of CPU performance Tomasz Buchert 1 Lucas Nussbaum 2 Jens Gustedt 1 1 INRIA Nancy Grand Est 2 LORIA / Nancy - Universit e Validation of distributed systems Approaches: Theoretical approach (paper and pencil) the most

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Accurate emulation of CPU performance

Tomasz Buchert1 Lucas Nussbaum2 Jens Gustedt1

1 INRIA Nancy – Grand Est 2 LORIA / Nancy - Universit´

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Validation of distributed systems

Approaches: Theoretical approach (paper and pencil)

the most general results and understanding very hard (leads to unsolvability results)

Experimentation (real application on a real environment)

realistic context, credibility difficulty of preparation and control, questionable reproducibility

Simulation (modeled application inside modeled environment)

very simple and perfectly reproducible experimental bias, possibly unrealistic

Emulation (real application inside a modeled environment)

control over the experiment parameters difficult

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Emulation

The perfect emulated environment should emulate (independently): Network bandwidth, latency, topology Performance and number of CPUs Memory capabilities Background noise (network, CPU, faults) Already implemented in Wrekavoc – a tool to define and control heterogeneity of the cluster (but not perfect yet!) In this talk, however, we specifically concentrate on

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Emulation

The perfect emulated environment should emulate (independently): Network bandwidth, latency, topology Performance and number of CPUs Memory capabilities Background noise (network, CPU, faults) Already implemented in Wrekavoc – a tool to define and control heterogeneity of the cluster (but not perfect yet!) In this talk, however, we specifically concentrate on

Emulation of CPU

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CPU emulation

Various elements of CPU architecture could be emulated: speed number of cores sizes and properties of caches (and topology thereof) memory access speed (especially for NUMA systems) In this talk, we will talk about

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CPU emulation

Various elements of CPU architecture could be emulated: speed number of cores sizes and properties of caches (and topology thereof) memory access speed (especially for NUMA systems) In this talk, we will talk about

Degradation of CPU speed

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An example

50 % Unused CPU 1 50 % Unused CPU 2 70 % Unused CPU 3 30 % Unused CPU 4 (1) controlling speed of each CPU/core independently

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An example (continued)

50 % Unused CPU 1 50 % Unused CPU 2 70 % Unused CPU 3 30 % Unused CPU 4 (2) being able to create separated scheduling zones

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Dynamic frequency scaling (CPU-Freq)

AKA Intel Enhanced SpeedStep or AMD Cool’n’Quiet Hardware solution to reduce:

heat noise power usage

For:

no overhead of emulation completely unintrusive meaningful CPU time measure

Against:

nly a finite set of different frequency levels

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CPU-Lim

Method available in Wrekavoc Algorithm:

if CPU usage ≥ threshold → send SIGSTOP to the process if CPU usage < threshold → send SIGCONT to the process

CPU usage = CPU time of the process

process lifetime

For:

easy and almost POSIX-compliant

Against:

intrusive and unscalable decision based on one process instead of global CPU usage sleeping is indistinguishable from preemption

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Fracas

Based on idea from KRASH (load injection tool) idea Uses Linux Cgroups and Completely Fair Scheduler A predefined portion of the CPU is given to tasks burning CPU All other processes are given the remaining CPU time

Emulated processes CPU burner Core 1 Emulated processes CPU burner Core 2 Emulated processes CPU burner Core 3 Tomasz Buchert, Lucas Nussbaum and Jens Gustedt Accurate emulation of CPU performance 9 / 20

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Fracas

Based on idea from KRASH (load injection tool) idea Uses Linux Cgroups and Completely Fair Scheduler A predefined portion of the CPU is given to tasks burning CPU All other processes are given the remaining CPU time For:

unintrusive scalable

Against:

unportable to other systems sensitive to the configuration of the scheduler

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Fracas and latency of the scheduler

1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0

CPU Frequency [GHz]

3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0

GFLOP / s

0.1 ms 1 ms 10 ms 100 ms 1000 ms

The smaller the latency, the better the emulation

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Evaluation

Based on different types of work:

CPU intensive (Linpack benchmark) IO bound multiprocessing multithreading memory speed (STREAM benchmark)

X-axis – emulated frequency Y-axis – speed perceived by the benchmark each test repeated 10 times, results = average 95% confidence interval using t-Student distribution Evaluation performed on Grid’5000 platform

nodes with two quad-core Intel Xeon X5570 processors nodes with a pair of single-core AMD Opteron 252 processors

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Grid’5000

GB / s

CPU-Freq CPU-Lim1 Fracas

Memory speed is affected differently by each method

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Summary of the evaluation

CPU-Freq:

very good results coarse granularity

CPU-Lim:

not scalable due to implementation, intrusive higher variance controls processes, not threads

Fracas:

good behavior for a single-task workload scalable bad behavior for multitask workload

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Future work

Explore other approaches Improve Fracas to cover multitasking Emulate memory bandwidth Emulate other aspects of CPU Integrate Fracas into Wrekavoc Take over the world :)

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Conclusions

Presented Fracas, a method for CPU performance emulation based on Linux cgroups Compared with CPU-Freq and CPU-Lim (Wrekavoc) Evaluated experimentally on Grid’5000 None of the methods is perfect:

CPU-Freq: coarse grained CPU-Lim: implementation problems, not scalable Fracas: works perfectly in single thread/process case, needs work in multithread/process case

Questions?

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