Presentation is loading. Please wait.

Presentation is loading. Please wait.

Effective mechanism for bufferless networks at intensive workloads

Published byJoanna Freeman Modified over 6 years ago

Similar presentations

Presentation on theme: "Effective mechanism for bufferless networks at intensive workloads"— Presentation transcript:

1 Effective mechanism for bufferless networks at intensive workloads
Rachata Ausavarungnirun, Kevin Chang

2 Problems (recap) Bufferless deflection flow control only performs well under light workloads Real applications contain a mixture of light and heavy workloads Latency and energy consumption increase significantly when there are several heavy workloads

3 Possible Solution Changing topologies Throttling the injection
Adding more links so flits can reach the destination sooner (Flattened butterfly) Increases the total network capacity Throttling the injection Be aware of the workload characteristics Prioritizing latency critical workloads over non latency critical workloads

4 Key Idea (Topology) Imposing a new topology that allows bufferless to be able to tolerate high intensity workloads BLESS networks with Flattened Butterfly can outperform buffered networks on a mesh (see results in the future slide) Require a good router design to efficiently operate the new topology The number of ports needed in Flattened butterfly scale as 2*SQRT(N)

5 FBFLY result

6 FBFLY disadvantages The number of port in each router increases by 2*sqrt(total nodes) This will increase the size of the router (crossbar, datapath, etc.) This increases the latency in the router Conclusion: FBFLY does not scale well with a large network

7 Throttling Problem Goal Solution
Network intensive applications contend for the shared resource with less intensive applications which are more critical Goal Reduce interference to increase system throughput Solution Prevent network intensive applications from injecting packets to avoid saturating the network

8 Throttling Key Ideas When the network is approaching the saturation point, start throttling Completely shut off the injection of intensive applications for some time intervals Reduce interference from intensive applications Guarantee of Fairness Allow network intensive applications to inject once in a while

9 Throttling Who? Applications with high L1 MPKI (misses per K instructions) An application with high L1 MPKI injects a large amount of packets Applications with high L1 MPKI are less sensitive to latency

10 Throttling (When?) Interval-based throttling
If totalMPKI < static threshold Free for all state, any node can inject flits Timeline FFA

11 Throttling (When?) If totalMPKI > static threshold
Start throttling high intensive applications Application with low MPKI can inject freely at any intervals Allow one application with high MPKI to run in each interval in a round robin manner Fine grain intervals Timeline FFA App1 App2 App1 App2

12 Throttling (When?) If totalMPKI > static threshold
Start throttling high intensive applications Application with low MPKI can inject freely at any intervals Allow one application with high MPKI to run in each interval in a round robin manner Fine grain intervals Timeline FFA App1 App2 App1 App2

13 Throttling (When?) If totalMPKI > static threshold
Start throttling high intensive applications Application with low MPKI can inject freely at any intervals Allow one application with high MPKI to run in each interval in a round robin manner Fine grain intervals Timeline FFA App1 App2 App1 App2

14 Throttling (When?) If totalMPKI > static threshold
Start throttling high intensive applications Application with low MPKI can inject freely at any intervals Allow one application with high MPKI to run in each interval in a round robin manner Fine grain intervals Timeline FFA App1 App2 App1 App2

15 Throttling (When?) Termination If totalMPKI < static_threshold_low
Termination point Timeline … … … Last App FFA

16 Questions?

17 Backup Slides

18 Throttling policy MPKI 2 10 40 1 15 53 4 8 45 Current MPKI Threshold
Throttle mode? 178 200 N

19 Throttling policy MPKI 3 10 63 2 15 76 8 73 Current MPKI Threshold
Throttle mode? 252 200 Y

20 Throttling Mode: Period 1
MPKI 3 10 63 2 15 76 4 8 73 Current MPKI Threshold Throttle mode? 252 200 N

21 Throttling Mode: Period 2
MPKI 3 10 63 2 15 76 4 8 73 Current MPKI Threshold Throttle mode? 252 200 N

22 Throttling Mode: Period 3
MPKI 3 10 63 2 15 76 4 8 73 Current MPKI Threshold Throttle mode? 252 200 N

23 Throttling Mode: Period 4
SlowDown 4.4 3.6 1.4 4.8 2.4 1.3 3.4 2.7 1.5 Injection Rate Threshold Throttle mode? low 4 Y

24 Throttling Mode SlowDown (updated) 2.7 1.2 1.8 3.2 1.1 1.5 1.4 2.3 1.7
Injection Rate Threshold Throttle mode? low 4 N

25

Download ppt "Effective mechanism for bufferless networks at intensive workloads"

Similar presentations

George Nychis✝, Chris Fallin✝, Thomas Moscibroda★, Onur Mutlu✝

George Nychis✝, Chris Fallin✝, Thomas Moscibroda★, Onur Mutlu✝
Interconnection Networks: Flow Control and Microarchitecture.

Interconnection Networks: Flow Control and Microarchitecture.
Prof. Natalie Enright Jerger

Prof. Natalie Enright Jerger
Adaptive Backpressure: Efficient Buffer Management for On-Chip Networks Daniel U. Becker, Nan Jiang, George Michelogiannakis, William J. Dally Stanford.

Adaptive Backpressure: Efficient Buffer Management for On-Chip Networks Daniel U. Becker, Nan Jiang, George Michelogiannakis, William J. Dally Stanford.
1 On-Chip Networks from a Networking Perspective: Congestion and Scalability in Many-Core Interconnects George Nychis ✝, Chris Fallin ✝, Thomas Moscibroda.

1 On-Chip Networks from a Networking Perspective: Congestion and Scalability in Many-Core Interconnects George Nychis ✝, Chris Fallin ✝, Thomas Moscibroda.
Application-to-Core Mapping Policies to Reduce Memory System Interference Reetuparna Das * Rachata Ausavarungnirun $ Onur Mutlu $ Akhilesh Kumar § Mani.

Application-to-Core Mapping Policies to Reduce Memory System Interference Reetuparna Das * Rachata Ausavarungnirun $ Onur Mutlu $ Akhilesh Kumar § Mani.
Misbah Mubarak, Christopher D. Carothers

Misbah Mubarak, Christopher D. Carothers
Energy Efficiency through Burstiness Athanasios E. Papathanasiou and Michael L. Scott University of Rochester, Computer Science Department Rochester, NY.

Energy Efficiency through Burstiness Athanasios E. Papathanasiou and Michael L. Scott University of Rochester, Computer Science Department Rochester, NY.
Application-Aware Memory Channel Partitioning † Sai Prashanth Muralidhara § Lavanya Subramanian † † Onur Mutlu † Mahmut Kandemir § ‡ Thomas Moscibroda.

Application-Aware Memory Channel Partitioning † Sai Prashanth Muralidhara § Lavanya Subramanian † † Onur Mutlu † Mahmut Kandemir § ‡ Thomas Moscibroda.
Flattened Butterfly Topology for On-Chip Networks John Kim, James Balfour, and William J. Dally Presented by Jun Pang.

Flattened Butterfly Topology for On-Chip Networks John Kim, James Balfour, and William J. Dally Presented by Jun Pang.
Aérgia: Exploiting Packet Latency Slack in On-Chip Networks

Aérgia: Exploiting Packet Latency Slack in On-Chip Networks
S-MAC Sensor Medium Access Control Protocol An Energy Efficient MAC protocol for Wireless Sensor Networks.

S-MAC Sensor Medium Access Control Protocol An Energy Efficient MAC protocol for Wireless Sensor Networks.
Evaluating Bufferless Flow Control for On-Chip Networks George Michelogiannakis, Daniel Sanchez, William J. Dally, Christos Kozyrakis Stanford University.

Evaluating Bufferless Flow Control for On-Chip Networks George Michelogiannakis, Daniel Sanchez, William J. Dally, Christos Kozyrakis Stanford University.
$ A Case for Bufferless Routing in On-Chip Networks A Case for Bufferless Routing in On-Chip Networks Onur Mutlu CMU TexPoint fonts used in EMF. Read the.

$ A Case for Bufferless Routing in On-Chip Networks A Case for Bufferless Routing in On-Chip Networks Onur Mutlu CMU TexPoint fonts used in EMF. Read the.
Allocator Implementations for Network-on-Chip Routers Daniel U. Becker and William J. Dally Concurrent VLSI Architecture Group Stanford University.

Allocator Implementations for Network-on-Chip Routers Daniel U. Becker and William J. Dally Concurrent VLSI Architecture Group Stanford University.
Random Access MAC for Efficient Broadcast Support in Ad Hoc Networks Ken Tang, Mario Gerla Computer Science Department University of California, Los Angeles.

Random Access MAC for Efficient Broadcast Support in Ad Hoc Networks Ken Tang, Mario Gerla Computer Science Department University of California, Los Angeles.
Multiple constraints QoS Routing Given: - a (real time) connection request with specified QoS requirements (e.g., Bdw, Delay, Jitter, packet loss, path.

Multiple constraints QoS Routing Given: - a (real time) connection request with specified QoS requirements (e.g., Bdw, Delay, Jitter, packet loss, path.
Network based System on Chip Part A Performed by: Medvedev Alexey Supervisor: Walter Isaschar (Zigmond) Winter-Spring 2006.

Network based System on Chip Part A Performed by: Medvedev Alexey Supervisor: Walter Isaschar (Zigmond) Winter-Spring 2006.
Power saving technique for multi-hop ad hoc wireless networks.

Power saving technique for multi-hop ad hoc wireless networks.
1 Algorithms for Bandwidth Efficient Multicast Routing in Multi-channel Multi-radio Wireless Mesh Networks Hoang Lan Nguyen and Uyen Trang Nguyen Presenter:

1 Algorithms for Bandwidth Efficient Multicast Routing in Multi-channel Multi-radio Wireless Mesh Networks Hoang Lan Nguyen and Uyen Trang Nguyen Presenter:

Similar presentations

Ads by Google