5G Network, GPU and FPGA

Notes Sharing

Richard T. Kuo

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Intent• Highlight few trends affect telecom infrastructure architecture:

• Digital Society• Big Data and Machine Learning

• List some enablers for evolving demand:• Edge Computing• Graphic Process Unit(GPU)• Field Programmable Gate Array (FPGA)

• Discuss some supporting architecture options:• Customize Nodes• Network Slicing

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Trends• Digitalization

• Virtualization• Physical -> digital -> data driven• IoE -> data 4V (volume, variety, velocity, veracity) -> analytics, optimization, ML

• Mobilization• Connectivity

• Unconnected -> mobile -> mobile optimized • Increase system scope/domain/complexity/interactions• Place -> People -> Devices• Automation -> self-directed/managing/healing • Mobility

• Time => anytime• space => anywhere• data => more available information/inference

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What Should 5G Bring

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5G Use Cases

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5G Main Enablers• Dynamic RAN provides a RAN that can adapts to rapid changes in user needs

and the mix of the generic 5G services.• Ultra-Dense Networks,• Moving Networks,• Devices acting as temporary as access nodes,• D2D communication for both access and backhaul.

• Lean System Control Plane (LSCP) provides new lean signaling/control information and allows separation of data and control information and support large variety of devices with very different capabilities.

• Localized Contents and Traffic Flows allow offloading, aggregation and distribution of real-time and cached content.

• Spectrum Toolbox contains a set of enablers (tools) to allow 5G systems to operate under different regulatory framework and share enablers.

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Data Process at Edge

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Edge Computing• Pushes applications, data and computing power (services) to the

logical extremes of a network. • Replicates fragments of information across distributed networks.

• Place customized nodes (SDR, SDN, NFV, …) closer to the client whenever it is possible.

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Edge Computing from: http://ubiquity.acm.org/article.cfm?id=2822875

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Advantages of Edge Computing• Decrease the data volume that must be moved, the consequent

traffic, and the distance the data must go, thereby reducing transmission costs, shrinking latency.

• Reduces or eliminates the network bottlenecks.• Fast response times.• Reduce security risk by reducing the non-essential data travels into

network core, only necessary data forward for analysis. • Deeper insights, with privacy control: Analyze sensitive data locally

instead of sending it to the cloud for analysis.

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5G Ecosystemfrom 5G-PPP-5G-Architecture-WP-For-public-consultation.pdf

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KT – Network Architecture Evolution 4G to 5Gfrom http://www.netmanias.com/en/?m=attach&no=13956

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KT - Network Architecture Evolution 4G to 5Gfrom http://www.netmanias.com/en/?m=attach&no=13955

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Edge Node Architecture (need design improvement, this is only a place holder)

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Graphics Processing Unit (GPU) • A GPU is a computer chip that performs rapid mathematical

calculations, primarily for the purpose of rendering images.

• A GPU generally has a large number of slow and weak processors (lower operating frequency, lower number of registers, simpler ALU's etc.)

• GPU's come strapped with lots of memory and generally have high memory bandwidth to support the hundreds of small processors that make up the GPU.

• GPUs are special purpose and can compute vector math, matrix math, pixel transforms and rendering jobs about 10-100x faster than the equivalent CPU performance as all these tasks are embarrassingly parallel.

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CPU vs GPUfrom http://www.electronicspecifier.com/communications/vivante-es-design-magazine-gpus-the-next-must-have

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Parallel Computing and StreamingThe Landscape of Parallel Computing Research: A View from Berkeley

The 13 application areas where OpenCL can be used

1. Dense Linear Algebra

2. Sparse Linear Algebra

3. Spectral Methods

4. N-Body Methods

5. Structured Grids

6. Unstructured Grids

7. Monte Carlo

8. Combinational Logic

9. Graph traversal

10. Dynamic Programming

11. Backtrack and Branch + Bound

12. Construct Graphical Models

13. Finite State Machine

14. …

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Current VPP Hardware Accelerationfrom https://fd.io/technology

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Field Programmable Gate Arrays (FPGAs) • Field Programmable Gate Arrays

(FPGAs) are semiconductor devices that are based around a matrix of configurable logic blocks (CLBs) connected via programmable interconnects.

• FPGAs can be reprogrammed to desired application or functionality requirements after manufacturing.

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FPGA Applications Partial Listfrom: http://www.xilinx.com/training/fpga/fpga-field-programmable-gate-array.htm

• Aerospace & Defense - Radiation-tolerant FPGAs along with intellectual property for image processing, waveform generation, and partial reconfiguration for SDRs.

• ASIC Prototyping - ASIC prototyping with FPGAs enables fast and accurate SoC system modeling and verification of embedded software

• Audio - Xilinx FPGAs and targeted design platforms enable higher degrees of flexibility, faster time-to-market, and lower overall non-recurring engineering costs (NRE) for a wide range of audio, communications, and multimedia applications.

• Automotive - Automotive silicon and IP solutions for gateway and driver assistance systems, comfort, convenience, and in-vehicle infotainment. - Learn how Xilinx FPGA's enable Automotive Systems

• Broadcast - Adapt to changing requirements faster and lengthen product life cycles with Broadcast Targeted Design Platforms and solutions for high-end professional broadcast systems.

• Consumer Electronics - Cost-effective solutions enabling next generation, full-featured consumer applications, such as converged handsets, digital flat panel displays, information appliances, home networking, and residential set top boxes.

• Data Center - Designed for high-bandwidth, low-latency servers, networking, and storage applications to bring higher value into cloud deployments.

• High Performance Computing and Data Storage - Solutions for Network Attached Storage (NAS), Storage Area Network (SAN), servers, and storage appliances.

• Medical - For diagnostic, monitoring, and therapy applications, the Virtex FPGA and Spartan® FPGA families can be used to meet a range of processing, display, and I/O interface requirements.

• Video & Image Processing - Xilinx FPGAs and targeted design platforms enable higher degrees of flexibility, faster time-to-market, and lower overall non-recurring engineering costs (NRE) for a wide range of video and imaging applications.

• Wired Communications - End-to-end solutions for the Reprogrammable Networking Linecard Packet Processing, Framer/MAC, serial backplanes,

• and more

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GPU and FPGA Considerations • GPU has good penetration on ML community. It needs to overcome big

inertia to get people move away from GPUs CUDA.• FPGAs uses less power, but new NVIDIA chips use as few as 10-15 watts

for a teraflop. • Verification of complex designs implemented on FPGA is a big challenge.

In contrast testing and validating CUDA code is relatively easier.• Fast digital design, no wait to obtaining a target chip. • The design can be implemented on the FPGA and tested at once. • FPGAs are good for prototyping. Design change change can be absorbed

in field.

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Observations and Interpretations• Add flexible Edge Computing Nodes for 5G network. • Use high computing power and customized SoC+FPGA for BTS/eNode-

B, and form a cluster/cloud to share resources.• Accelerate performance with Field Programmable Gate Array.• Adapt Software Defined Radio and dynamic RAN.• Leverage GPUs for distributed data analytics and ML.• Consider Micro-HPC (High Performance Computing) data center for

deployment.

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Supplementary Material

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5G

1000xMobile Data

Volumes

10x-100xConnected Devices 5x

Lower Latency

10x-100xEnd-user Data Rates

10xBattery Life for Low

Power Devices

Source: METIS

Evolution Towards 2020

4G3G2G

© Telefonaktiebolaget LM Ericsson 2015 | Ericsson June 2015

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5G RequirementsBusiness Requirements• Massive broadband (xMBB) that delivers

gigabytes of bandwidth on demand <- velocity

• Massive machine-type communication (mMTC) that connects billions of sensors and machines <- variety + volume

• Critical machine-type communication (uMTC) that allows immediate feedback with high reliability and enables for example remote control over robots and autonomous driving. <- velocity + veracity

Technology Requirements• 1-10Gbps connections to end points in the

field (i.e. not theoretical maximum)• 1 millisecond end-to-end round trip delay

(latency)• 1000x bandwidth per unit area• 10-100x number of connected devices• (Perception of) 99.999% availability• (Perception of) 100% coverage• 90% reduction in network energy usage• Up to ten year battery life for low power,

machine-type devices

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Comparison between 1g, 2g, 3g, 4g and 5g

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5G mMBB Requirements and Technology Enablers• Software Defined Radio (SDR) -> multiple radio technologies.• Massive multiple-input and multiple-output (MIMO) antennas -> data

throughput and capacity• Dynamic RAN

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Logic Gates

Truth Table FPGA

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Binary Adderfrom: http://cpuville.com/adder.htm

Truth Table Gates for Adder

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FPGA Development BoardMercury FPGAFrom: http://www.micro-nova.com/mercury/

Terasic SoCKit Altera Cyclone V + Dual Core A9From: http://www.cnx-software.com/2013/08/15/249-terasic-sockit-development-kit-features-altera-cyclone-v-sx-dual-core-a9-fpga-soc/

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Programming FPGA

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