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Micro-Architecture Techniques for Sensor Network Processors Amir Javidi EECS 598 Feb 25, 2010
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2 Motivation Low performance tasks Long duration Small energy supplies
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3 Papers [1] L. Nazhandali, B. Zhai, J. Olson, A. Reeves, M. Minuth, R. Helfand, S. Pant, T. Austin, and D. Blaauw, “Energy optimization of subthreshold voltage sensor network processors,” in Proc. Int. Symp. Computer Architecture, 2005, pp. 197–207. [2] S. Hanson, M. Seok, Y-S. Lin, Z. Foo, D. Kim, Y. Lee, N. Liu, D. Sylvester, and D. Blaauw, “A low voltage processor for sensing applications with picowatt standby mode,” IEEE Journal of Solid- State Circuits, pp. 1145-1155, April 2009.
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4 Energy Budget 2g Vanadium oxide battery: 720 mAh Powers ARM 720T processor at 100MHz for 45hrs Thin film zinc/silver oxide battery: 100 μAh/cm 2, 1.55 V For area of 1mm 2 average current must be 114pA (power consumption of 177 pW) for 1 year lifetime
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5 Performance Requirement Blood pressure monitoring (low rate): Sensing @ 800 bps 10,000 inst/sec EEG brain signal monitoring (high rate): 3200 bps 56,000 inst/sec for filtering, analysis, compression, and storage
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6 Architecture/Circuit Techniques Sub-threshold implementation (V dd < V th ) ISA optimization Voltage scaling Power gating Stack forcing Data/instruction compression
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7 Subthreshold design Why subthreshold? Processor operating in lowest super-threshold voltages deliver too much performance Performance of sensor network processor applications on embedded targets. Number of times faster than real-time the processor can handle the worst case data stream rate [1].
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8 Subthreshold Circuit Design
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9 Subthreshold Energy Optimization Subthreshold Energy as a function of Voltage[1] V min energy optimal supply voltage
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10 ISA Optimization Why ISA optimization? Memory dissipates static/dynamic energy Memory size leakage Tradeoff between memory size and control logic size Logic Vs memory energy tradeoff [1]
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11 ISA Optimization Impact of ISA optimization on code size and control logic complexity
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12 Micro-Architecture Sensor network processor micro-architecture
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13 Performance vs. Energy
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14 Results Sensor network processor ROM/RAM memory 8 bit data path 235 mV supply 182 KHz 1.38 pJ/inst 4.1x faster than necessary for mid-bandwidth 25 years lifetime with 2g vanadium oxide battery (720 mAh)
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15 Phoenix Processor Focus on lowering standby power Older 0.18μm technology Custom leakage-optimized instruction set Simple data memory compression Ultra-low-leakage memory cell Huge tradeoff between standby power and area and active energy
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16 Phoenix Processor
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17 CMOS Technology Newer technology (65 nm) High subthreshold leakage Small capacitance Older technology (180 nm) 7.7x larger 647x less total energy consumption
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18 Voltage Scaling Supply voltage of 0.5 V Mix of subthreshold and near-subthreshold devices Retentive gates high-V th ~ 0.7 V Non-retentive gates medium-V th ~ 0.5 V High-V th consumes ~ 1000x less leakage power
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19 Power Gating Medium-V th power switch Smaller switch ~ 1000x Less area overhead Less charging/discharging power overhead
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20 CPU Architecture 2 stage, 8bit data width, 10bit inst. Width ALU (add, subtract, shift) No multiplier Simple decoder (min set of operations)
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21 ISA Optimization Minimized instruction width (10 bit) Reduces IMEM standby power dissipation Efficient operand encoding Explicit operand: more flexibility, more frequently used Implicit operand: less flexibility, less frequently used
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22 Memory Design 64x10b SRAM (IMEM) Application specific instructions No power gating 64x10b ROM (IROM) Commonly used instructions Power gated 52x40b SRAM (DMEM) Data compression Fine grain power gating
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23 Memory Design Leakage reduction High-V th bitcell transistors Cross coupled inverters: Stacked transistors Increased length (0.35μm to 0.50μm) ~2x leakage reduction Robustness Full swing read-buffer Power gated
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24 Results Phoenix processor 0.5 V power supply 106 KHz 2.8 pJ/cycle 297 nW 226 nW active mode 35.4 pW standby mode 915 x 915 μm 2
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