Efficiency Metrics for Design Space Exploration of Wireless Baseband Processing

Transcription

1 MPSoC 0 Nagaragawa Convention Center Gifu City, Japan Efficiency Metrics for Design Space Exploration of Wireless Baseband Processing Norbert Wehn //ems.eit.uni-kl.de Metric - Computational Requirements 0000 Example - Mobile Phone Trends for Channel Decoding Algorithmic operations/bit umts umts hsdpa wimax lte lte-a td-scdma dmb-t n cdma2000 wcdma 802.6e dvb-h dvb-c dvb-s dab td-scdma 802.b dvb-t 802.a uwb 00 gsm gprs 0. GOPS dvd 0 0 GOPS cellular decoders bluetooth blueray broadcast decoders connectivity decoders Datarate Mbps Source: Kees van Berkel, DATE2009

2 Metric Energy Efficiency Example - SODA, DSP and GP Architectures 3 Area- and Energy Efficiency Design Space 0 better energy LTE TC (50Mbit/s) better overall operation/energy (op/pj) LDPC WiMedia (~Gbit/s) CC (500Mbit/s) -3-Min better area 0, Area Efficiency: GOPs/mm 2 4 2

3 Assessment Metrics are computation centric i.e. operations are counted only On the other hand SoC are becoming more and more interconnect centric e.g. NoC more and more memory centric Assessment of these metrics Various channel decoder research group All architectures based on standard synthesis flows All designs based on 65nm technology@worst case All data in-house available 5 Overview Channel Decoders Decoder Flexibility Max Blocksize Payload Throughput [Mbit/s] Freq. [MHz] Area [mm2] Dynamic Power [mwatt] ASIP Conv. Codes Binary TC Duo-binary TC N=6k 40 4(6iter) 28(6iter) LTE Turbo LTE turbo code N=8k 50 (6iter) LDPC flex R=/4 to R=9/0 N=6k (20-0iter) LDPC fixed R=3/4 N=.2k 480 (6iter) 435 LDPC WiMedia.5 R=/2-4/5 N=.3k 640 (R=/2,5iter) 960 (R=3/4,5iter) ~00 ~300 ~389 ~ ~93 CC Decoder 64-state NSC ~37 6 3

4 Algorithmic Throughput Calculations [GOPs] Code Operations per decoded information bit normalized to ~8bit addition Infobit-Throughput Giga operations per second [GOPs] 00Mbit/s 300Mbit/s Gbit/s CC: states=64 LDPC () (x3.4 appr. BP) Turbo (Max-Log) ~200 ~20 ~ 60 ~200 5 iter 75/R ~7.5/R ~22.5/R ~ 75/R 0 iter 50/R ~5/R ~ 45/R ~ 50/R 20 iter 300/R ~ 30/R ~ 90/R ~ 300/R 40 iter 600/R ~ 60/R ~ 80/R ~ 600/R 2 iter 280 ~ 28 ~ 84 ~ iter 560 ~ 56 ~68 ~ iter 840 ~ 84 ~252 ~ Area- and Energy Efficiency 0 ASIP TC (4Mbit/s) operation/energy (op/pj) LTE TC (50Mbit/s) LDPC flexible (~00 Mbit/s) LDPC WiMedia (~Gbit/s) CC (500Mbit/s) -3-Min Area Efficiency: GOPs/mm 2 8 4

5 What about Memory/Data Transfers Current metric: energy = only operations/energy Data transfers/ accesses substantially contribute to the power consumption Example (R=0.5) 50 Mbit/s Turbo: ~26 Gops ~40 Gaccesses 50 Mbit/s LDPC : ~90 Gops ~80 Gaccesses Efficient data transfer is key for efficient implementation E.g. LTE TC: special interleaver structure to avoid access conflicts E.g. DVB-S2/WiMAX LDPC: special code structure to minimize access conflicts Efficiency metrics based only on operations are not appropriate Power includes operations and accesses! Architectures are favored where operations dominate compared to accesses Turbo decoder will always be evaluated to be more efficient Same argumentation for area 9 System Oriented Area- and Energy Efficiency 0 better energy LTE TC (50Mbit/s) better overall coded bit/energy (bit/nj) Dec LDPC WiMedia (~Gbit/s) Energy : decoded information bit per energy CC (500Mbit/s) Area : decoded information bit/s per area -3-Min better area 0, Area Efficiency: (Mbit/s)/mm 2 0 5

6 Decoders in System Design Space 00 ) ecoded bit/energy (bit/nj) de 0 ASIP TC (4Mbit/s) LTE TC (50Mbit/s) LDPC flexible (~00 Mbit/s) LDPC WiMedia (~Gbit/s) CC (500Mbit/s) -3-Min Area Efficiency: (Mbit/s)/mm 2 Observations Large change in relative and absolute positions can be observed Relative positions between and λ-3-min changed Efficiency difference between and λ-3-min decreases LDPC WiMedia decoder has a much larger than the flexible LDPC decoder Efficiency of LDPC WiMedia decoder is not far away from CC decoder But what about communications performance in the comparisons? Overall of a baseband receiver depends on Communications performance Implementation performance (area- and energy ) Flexibility 2 6

7 Comparison of Different Architectures Scenario : Communication driven Comparison of two iterative decoders (TC versus LDPC) Identical communications performance Different parameters (code rate, iterations) impact on implementation Scenario 2: Implementation driven Comparison of iterative and non-iterative decoders (LDPC versus CC) 64-state convolutional code 960 Mbit/s (WiMedia.2) and WiMedia.5 LDPC decoder Varying communication performance impact on implementations 3 Scenario : Fixed Communication Performance Turbo Code LDPC Code Blocksize 645 Information bits, TC: iterations 4 7

8 Scenario : Implementation Efficiency 0 J) ecoded bit/energy (bit/n 0. TC constant for all code rates, 6.5 iter R=/2, 20 iter R=4/5, 0 iter dtc R=/3, 40 iter LTE flexible LDPC Area Efficiency: (Mbit/s)/mm2 5 Scenario 2: Varying Communication Performance Simulation Set-Up: WiMedia.5 chain, 6-QAM, Blocksize 200 Information bits 6 8

9 Scenario 2: Implementation Efficiency coded bit/energy (bit/nj) dec 00 4dB worse com. Perf. (iter) Identical Throughput (e.g. clock gating) Identical comm. Perf. (2iter) Identical 0 throughput (e.g. clock gating) 4dB worse com. Perf. (iter) 5 times higher throughput Identical com. Perf. (2iter) 2.5 times higher throughput 4dB better com. Perf. (5iter) Identical throughput LDPC WiMedia.5 CC WiMedia Area Efficiency: (Mbit/s)/mm2 7 Summary Understanding trade-offs between implementation, communications performance and flexibility requirements is mandatory for efficient i baseband b receivers Operation based metrics for energy and area can be misleading Memory and data transfers have to be considered in metrics for design space exploration Implementation metrics have to be linked to application performance Implementation of an architecture yields a trajectory 8 9