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KnightShift : Enhancing Energy Efficiency by Shifting the I/O Burden to a Management Processor. Sabyasachi Ghosh Mark Redekopp Murali Annavaram Ming-Hsieh Department of EE USC http://usc.edu/dept/ee/scip. Outline. Datacenter energy concerns Direct-attached storage issues

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slide1

KnightShift: Enhancing Energy Efficiency by

Shifting the I/O Burden to a Management

Processor

SabyasachiGhosh

Mark Redekopp

Murali Annavaram

Ming-Hsieh Department of EE

USC

http://usc.edu/dept/ee/scip

slide2

Outline

  • Datacenter energy concerns
    • Direct-attached storage issues
  • KnightShift solution
    • IPMI
    • Modifications to IPMI
  • Trace description
  • Results
  • On-going work andconclusions

|3

slide3

Datacenter Energy Concerns

  • Datacenter energy costs are a key concern
  • Common-case utilizations are very low, but not zero
  • Servers are not energy efficient at low utilizations
  • Consolidation and power-down are effective solutions
    • Long wakeup latencies from shutdown/low power modes are being mitigated
  • Except, Direct-attached storage (DAS) datacenters can not benefit from consolidation

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slide4

Direct-Attached Storage Architecture

Data is distributed on disks attached to individual nodes

Client requests arrive at a load balancer (1)

Load balancer assigns the request to one node (2)

Satisfying a request requires data from multiple nodes (3a)

Each remote node gets the data request

Remote nodes access their local disks (3b)

Generate response to the requestor

Requestor performs necessary computation on the consolidated data

Sends a response to the client (4)

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slide5

Server Power under DAS

  • Servers show lack of energy proportionality at low utilization
    • Power at 10% utilization is (much) more than 10% of the power at peak utilization
  • Energy proportionality is not just a CPU problem
    • Memory, disks, fans are one major source of power consumption
    • Motherboard components (voltage regulators, PCI slots) also consume power
  • CPUs are in fact becoming more energy proportional
    • Power scales to a limit using DVFS, clock gating,..
  • Achieving energy proportional server requires putting all motherboard components to sleep

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slide6

KnightShift as a Solution

  • KnightShift: Handle remote I/O requests using low power subsystem
    • Main server sleeps during low utilization while maintaining availability of data on the disks
  • Low power subsystem is called the Knight
  • Knight has the following properties
    • Closely attached to the main server to access its disk data
    • Electrically isolated from main server
    • Capable of receiving, interpreting, servicing remote request
    • Transparent to outside world

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slide7

Intelligent Platform Management Interface

  • Intelligent Platform Management Interface (IPMI) is a widely-implemented standard for out-of-band server management
    • Admins can remotely monitor server health with sensors, power on/off the server, install software
  • At the core of IPMI is Baseboard Management Controller (BMC)
    • BMC uses the same network interface as the primary system and even the same IP address
    • Embedded CPU, flash memory, separate power rails

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slide8

IPMI as a Knight

IPMI satisfies most properties of a Knight

Electrically isolated

transparently handles network packets

However, it does not have access to the primary server disks

Modify IPMI

Modify IO Hub with 2-input mux which switches between primary and Knight as needed

BMC must be able to handle disk access requests and be able to understand a few filesystems

BMC is already highly capable and can do complex network packet filtering

Knight capabilities further enhanced when BMC supports the same ISA

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slide9

Using Knight for System-level Power Saving

  • Primary server memory turned off
    • BMC’s flash memory to use as I/O buffers
    • Dirty disk data cached in primary memory drained to disk
  • Knight can handle even non-I/O requests
    • Requests with limited compute demands
    • Support the same ISA
      • IBM ASMA supports full ISA
  • Knight best for handling stateless workloads
      • Many e-commerce transactions are stateless
  • Significantly increases primary server sleep time by turning off the entire server (except disks), not just any single component

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slide10

Trace Based Evaluation

  • Minute-granularity utilization traces from USC's production datacenter
    • Compute, mail and NFS file server cluster
    • In particular, clusters use DAS
    • Detailed SAR traces collected for 9 days
  • Servers underutilized as can be seen from the graph
    • 10% CPU utilized for nearly 90% of the time

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slide11

CPU Utilization vs. System Utilization

  • CPU utilization is closely tied to overall system utilization (shown also in prior work (Fan2007)
  • Figure shows CPU utilization on Y-axis and disk utilization on secondary Y-axis for SCF

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slide12

Ideal Case Power Savings

  • Derived power versus utilization for current servers from SpecWEB power benchmarks
  • Assume power consumption in ideal servers scales quadratically with performance
    • Ideal machine power at 1/10 utilization is 1/100 of the peak power
  • Huge gap between current and ideal system power consumption

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slide13

KnightShift Power Savings

Primary Server ON

Knight ON

  • When trace shows CPU utilization < 10% assume Knight is ON
    • Knight power is constant at 1/100 of primary server power
  • When trace shows CPU utilization > 10% assume primary is ON
    • Primary server power is proportional to utilization (based on current server data from SpecWEB)
    • At wakeup primary consume 100% power

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slide14

Power Savings vs Performance Degradation

  • Response time grows when operating with Knight
    • Assuming a range of Knight capabilities the response time increases to 11% of the original time
  • Energy savings increase as Knight becomes more capable, giving more opportunities for the primary server to sleep

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slide15

Conclusion

  • Datacenter energy consumption is a serious concern
  • Consolidating and powering down idle servers is an effective approach
    • Does not work for direct-attached storage datacenters
  • KnightShift uses IPMI based BMC as a low power subsystem to handle remote I/O
    • Knight exploits IPMI’s unique characteristics to handle remote I/O requests
  • Trace based evaluation to study the current headroom
    • Traces collected for 9 days from USC datacenter for several clusters
    • Headroom studies show 2.5X improvement in energy consumption with Knight
  • Going forward plan to use a mix of analytical (queuing) models and emulation based implementation of KnightShift

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