CSC/ECE 506 Spring 2012/12b ad: Difference between revisions

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2D mesh networks are used when the scale of the network topology breaks into “larger-than-medium” scale. This is especially true when the dimensions are divisible by a factor two, as the benefit in the number of hops versus a traditional ring network can be tremendous.
2D mesh networks are used when the scale of the network topology breaks into “larger-than-medium” scale. This is especially true when the dimensions are divisible by a factor two, as the benefit in the number of hops versus a traditional ring network can be tremendous.


For example, in a worst-case scenario a sixteen-core multiprocessor would require eight hops to get to the farthest node. In a 2D mesh, however, creating a 4x4 grid guarantees that the maximum number of hops is six. Assuming random data distributed evenly among the cores, the expectation value (1/16 chance for each node) of the number of hops in a ring would be 3.6 (1/16*[0+1+2+3+... hops]), whereas the expectation value for the 2D mesh in minimal path would be 2.8. This benefit, though, comes at the necessary cost of increased power for the extra processing required.
For example, in a worst-case scenario a sixteen-core multiprocessor would require eight hops to get to the farthest node. In a 2D mesh, however, creating a 4x4 grid guarantees that the maximum number of hops is six. Assuming random data distributed evenly among the cores, the expectation value (1/16 chance for each node) of the number of hops in a ring would be 3.6 (1/16*[0+1+2+3+... hops]), whereas the expectation value for the 2D mesh in minimal path would be 2.8. This benefit, though, comes at the necessary cost of increased power for the extra processing required. A potential solution to this "power problem" is to group cores together in what is called a concentrated mesh, but even that requires increased crossbar complexity<ref name="GrotKeckler"/>.


===Flattened Butterfly===
===Flattened Butterfly===

Revision as of 02:28, 24 April 2012

On-chip Interconnects

Introduction

The content of this article is under active development will be updated regularly until the resubmission deadline.

As the number of processors in multiple-processor systems increases, increasing consideration needs to be given to how those processors communicate. With current technology, for a small number of processors shared-memory arrangements are quite effective. However, as the number of processors increases contention for available resources (memory, bus time, etc) increases, negatively impacting performance of the system. However, keeping these processors all on the same physical piece of hardware is convenient and helps performance due to physical proximity. As such, it is desirable to design hardware where many cores are part of the same die while allowing for the performance gains possible with interconnections. Recently there has been more research into these on-chip interconnects, and this article will explore the state of those efforts.

Topologies

The intracacies of semiconductor design and layout afford many different kinds of possible layouts when creating networking topologies on SoCs. Specifically, designs need to be amenable to creation on a two-dimension substrate, and as such practically limits the use of some more advanced topologies like hypercubes <ref name="GrotKeckler">Grot and Keckler, Scalable On-Chip Interconnect Topologies</ref>.

Rings

Ring topologies can be effective when the “number of cores is still relatively small but is larger than what can be supported using a bus” [Solihin 409]. Such cases are considered to use “medium-scale” interconnection networks.

Meshes

2D mesh networks are used when the scale of the network topology breaks into “larger-than-medium” scale. This is especially true when the dimensions are divisible by a factor two, as the benefit in the number of hops versus a traditional ring network can be tremendous.

For example, in a worst-case scenario a sixteen-core multiprocessor would require eight hops to get to the farthest node. In a 2D mesh, however, creating a 4x4 grid guarantees that the maximum number of hops is six. Assuming random data distributed evenly among the cores, the expectation value (1/16 chance for each node) of the number of hops in a ring would be 3.6 (1/16*[0+1+2+3+... hops]), whereas the expectation value for the 2D mesh in minimal path would be 2.8. This benefit, though, comes at the necessary cost of increased power for the extra processing required. A potential solution to this "power problem" is to group cores together in what is called a concentrated mesh, but even that requires increased crossbar complexity<ref name="GrotKeckler"/>.

Flattened Butterfly

Design Considerations

Energy Consumption

Multi-processor SoCs require additional energy in order to operate the on-chip interconnection hardware like routers. Too, the links between components can introduce increased losses in regards to required voltages and physical arrangement. Indeed, "on-chip network power has been estimated to consume up to 28% of total chip power" due to "channels, router fifos and router crossbar fabrics"<ref name="GrotKeckler" />. Simple topologies use less power due to simpler routers, but the increased number of hops can lead to overal increased power consumption.

Scalability

Scalability ties back to both energy and cost, but also to engineering constraints as well. Specifcally, the architecture needs to be sensitive to the power and heat requirements of the design, as well as the physical die size. Further, the design requires the ability to be fabricated predictably and within reasonable costs. To mitigate some of these factors, concentration of network interfaces can be employed, where a network interface is shared by multipe terminals. Efforts to scale more complicated topologies like the butterfly (into a "flattened" butterfly) have yielded promising results, but at the expense of too much energy expenditure<ref name="GrotKeckler" />.

Modern Implementations

Tilera

Intel MIC and ISOF

<ref name="intelisof">Intel Challenges ARM with IP and Interconnect Strategy</ref>

Summary

See Also

References

<references></references>