Slide 1 IoT Energy Savings with GZIP IP

Using GZIP Data Compression to Reduce Power Consumption in IoT Devices

Meredith LuckyVP of SalesCAST, Inc.

December 2016www.cast-inc.com

Slide 2 IoT Energy Savings with GZIP IP

Second Generation IoTThe First Generation was trying to get a product to market ASAP.The Second Generation is about product differentiation.

Low powerProcessing power in edge devicesReduced cost (less memory, smaller devices)

Slide 3 IoT Energy Savings with GZIP IP

A Typical IoT Node

Low Energy Consumption is a key factor

Slide 4 IoT Energy Savings with GZIP IP

Where is Energy Consumed?

RF Transceivers and NVMs are major energy consumers

MCU (no NVM or RF)0.5–5mA

Low-power RF10–30mA

Low-power Serial Flash

2–25mALow-power CPU0.1–1 nAmA

Slide 5 IoT Energy Savings with GZIP IP

Reducing the Energy Consumed via Compression

NVM: Firmware CompressionLess on-chip data to transfer = lower energy (and less time) to boot/wake-up

NVM: Data Storage CompressionLess off-chip data = faster R/W operations = lower energy

RF: Tx/Rx Data CompressionLess data to send/receive = lower RF active time = lower communication energy

Slide 6 IoT Energy Savings with GZIP IP

IoT Node with GZIP Accelerator

GZIP CompressionStandard for

interoperabilityHardware

AccelerationLower power

consumption, less processor overhead,

low latencyUsesNVM: Firmware decompression while code shadowingNVM: data compression for local data storageRF: data compression at application level or in networking stack

Slide 7 IoT Energy Savings with GZIP IP

Expected Energy GainsDepends on compression performance (ratio), which depends on Data Characteristics and Compression Algorithm ParametersBasic GZIP Compression Parameters:

Static or Dynamic Huffman Static: smaller siliconDynamic: higher compression

History WindowSmaller: smaller siliconLarger: higher compression

Low silicon overhead = Static Huffman and relatively small History Window

Slide 8 IoT Energy Savings with GZIP IP

How Compressible is Wireless Data?

IoT Devices typically Exchange a set of measurements/sensed dataAre able to receive commands, and May allow remote access via an HTML page

Data they transmit resembles text files, spreadsheets, and HTML These all compress nicely to levels of 3:1 even for Static Huffman and Small History Windows

Slide 9 IoT Energy Savings with GZIP IP

How Compressible Is Firmware?Three examples:

FreeRTOS Port and Sensor Control app on BA22-DE Cygnal FreeRTOS Port and demo app on 8051 InterNiche Tech. TCPI/IP and HTTP Stacks on Cortex-M3

Slide 10 IoT Energy Savings with GZIP IP

Energy and Boot Time Savings from Firmware Compression

GZIP Assumption: Static Huffman, 2KB HistoryNVM Assumptions: 1.8V Serial, 5mA Read Current, 50MHz Read Clock

Code Size in kBytes Required NVM Size

System #1

(8051)System #2

(BA2)System #3

(ARM)System #1

(8051)System #2

(BA2)System #3

(ARM)Uncompressed Code 25.5 161 985 256kbits 2Mbit 8MbitsCompressed Code 10.9 76 511 128kbits 1Mbit 4MbitsSavings 57.25% 52.80% 48.12% 54.25% 50.00% 50.00%

Boot Time in msec Boot Power in mA - sec

System #1

(8051)System #2

(BA2)System #3

(ARM)System #1

(8051)System #2

(BA2)System #3

(ARM)Uncompressed Code 3.98 25 154 0.02 0.13 0.77Compressed Code 1.7 12 80 0.01 0.06 0.4Savings 57.29% 52.00% 48.05% 57.25% 52.80% 48.12%

averages

Code Size

52.72%NVM Size

51.42%Boot Time

52.45%Boot

Power52.73%

Slide 11 IoT Energy Savings with GZIP IP

Data Storage Servers & Gateways

Move analytics from cloud to edge for faster response and bandwidth limited applications -> Requires local data storage instead of sending data to remote server

Slide 12 IoT Energy Savings with GZIP IP

Local Data Storage for Analytics

Store data from many edge sensor devices. Wake-up server for periodic analytic processingNo longer just simple log data, but much larger imagery and natural language dataCompression minimizes the amount of NVM, but also power of read/write operations for 2KB Page for Block of 64 pages = 128kB

Access time

us/pagePower

uJ/pagePower

uJ/block

Read 130.9 4.72 302

Write 405.9 38.94 2,492

Power example in Micron SLC NAND

Slide 13 IoT Energy Savings with GZIP IP

Energy Saving VS Duty Cycles

**

*

* Energy decreased 50%

Slide 14 IoT Energy Savings with GZIP IP

ConclusionCompression can be used to significantly decrease the energy consumption in IoT Nodes

Firmware Compression for devices using code shadowingCompression of local Data for edge analyticsCompression of Data exchanged over wireless links

Parameters that need to be evaluatedCompression algorithm and parametersCompressibility of dataSystem’s energy profile (duty cycle)

GZIP/GUNZIP IP cores available from CAST are perfectly suitable for IoT Nodes

Slide 15 IoT Energy Savings with GZIP IP

GZIP Cores From CASTLow latency: from 20 cycles FIFO latencyLow silicon requirements: ~22kGates for gzip or gunzip (Static Huffman and History Windows sizes up to 4096 Bytes)Low power: 160 MBytes/sec at just 10 MHzEasy integration: AXI-Streaming (AXI-ST), or AHB Interfaces