DSP base-station comparisons

Second generation (2G) wireless 2 nd generation: digital: last decade: 1990’s Voice and low bit-rate data –~14.4 – 28.8 Kbps Single standard –GSM (Europe) –CDMA (Qualcomm) –TDMA (Nokia) Power: –Max. active power < 500 mW (300 mW RF, 200 mW baseband) –Standby power < 50  W (0.01%) Simple algorithms (KOPs in ms)

3G devices – almost there Voice, high bit-rate data, multimedia –~100’s of Kbps (10x) Multi-standard –GSM/TDMA/CDMA on same chip Power : –Max. 500 mW Bandwidth is expensive! –Sophisticated algorithms for high spectral efficiency (bits/s/Hz) More baseband processing in less time (MOPs in  s )

4G mobile devices Year : Multiple antenna systems Handset data rates –~1-10 Mbps (10x) Multi-standard and multiple environments –GSM/EDGE/CDMA/TDMA/Wireless LAN/Bluetooth/Cable/DSL – work with the fastest, cheapest service you can get! Power consumption: –Max. 500 mW More sophisticated algorithms at higher data rates More baseband processing in lesser time (GOPs in ns)

Builds on the Imagine architecture

Imagine’s arithmetic clusters VLIW control 3 adders, 2 multipliers, 1 divider Scratch-pad and communication unit Distributed register files

Programming model Kernels –Computation KERNEL example1(istream a, istream b, ostream c) { loop_stream(a) { int ai, bi, ci; a >> ai; b >> bi; ci = ai * 2 + bi * 3; c << ci; } Streams –Communication void main() { Stream a(256); Stream b(256); Stream c(256); Stream d(1024);... example1(a, b, c); example2(c, d);... }

SWAP differences from Imagine Dynamically variable clusters to exploit data parallelism No external memory (SDRAM) or cache Network Interface replaced by RF Interface Fixed-point arithmetic Customization of units for high functional unit utilization

Potential advantages Power –Doing less work! (no parallelism overhead) –Application-specific units (higher FU) –Lower clock frequency (< 1/2) –Can use fewer clusters Area –Fewer unnecessary units –Fewer clusters

Optimizations Task pipelining –Time and power savings Specialized Functional units –Time and power savings Specialized interconnections –Little time savings but power savings

Re-ordering for parallel Viterbi X(0) X(2) X(4) X(6) X(8) X(10) X(12) X(14) X(1) X(3) X(5) X(7) X(9) X(11) X(13) X(15) X(0) X(1) X(2) X(3) X(4) X(5) X(6) X(7) X(8) X(9) X(10) X(11) X(12) X(13) X(14) X(15) b. Shuffled Trellisa. Trellis X(0) X(1) X(2) X(3) X(4) X(5) X(6) X(7) X(8) X(9) X(10) X(11) X(12) X(13) X(14) X(15) X(0) X(1) X(2) X(3) X(4) X(5) X(6) X(7) X(8) X(9) X(10) X(11) X(12) X(13) X(14) X(15)

Communication pattern Data re-arrangement problems forms a common communication pattern Odd-even permutation of the data Similar patterns observed for matrix transposes and for packed operations on finite-precision data

Future algorithms

Outline Design Methodology Programmable architecture design –Scalable Wireless Application-specific Processors (SWAPs) Applications to base-stations and handsets

Outline Design Methodology Programmable architecture design –Scalable Wireless Application-specific Processors (SWAPs) Applications to base-stations and handsets

Outline Design Methodology Programmable architecture design –Scalable Wireless Application-specific Processors (SWAPs) Applications to base-stations Handset SWAPs (H-SWAPs)