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Lower Power Design Guide. 1998. 6.7 성균관대학교 조 준 동 교수 http://vlsicad.skku.ac.kr. Contents. 1. Intoduction Trends for High-Level Lower Power Design 2. Power Management Clock/Cache/Memory Management 3. Architecture Level Design Architecture Trade offs, Transformation

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Lower power design guide

Lower Power Design Guide

1998. 6.7

성균관대학교 조 준 동 교수

http://vlsicad.skku.ac.kr


Contents
Contents

  • 1. Intoduction

  • Trends for High-Level Lower Power Design

  • 2. Power Management

    • Clock/Cache/Memory Management

  • 3. Architecture Level Design

    • Architecture Trade offs, Transformation

  • 4. RTL Level Design

    • Retiming, Loop-Unrolling, Clock Selection, Scheduling, Resource Sharing, Register Allocation

  • 5. partitioning

  • 6. Logic Level Design

  • 7. Circuit Level Design

  • 8. Quarter Sub Micron Layout Design

    • Lower Power Clock Designs

  • 9. CAD tools

  • 10. References


1 introduction

1. Introduction


Motivation

Portable Mobile (=ubiquitous =nomadic)

Systems with limited for heat sinks

Lowering power with fixed performance: DSPs in modems and cellular phones

Reliability: Increasing power ! increasing electromigration, 40-year reliability guarantee (product life cycle of telecommunication industries)

Adding fans to reduce power cause reliability to plummet.

Higher power leads to higher packaging costs: 2-watt package can be four times greater than a 1-watt package

Myriad Constraints: timing, power, testability, area, packaging, time-to-market.

Ad-Hoc Design: Lack a systematic process leading to universal applicability.

Motivation



Power dissipation in vlsi s
Power Dissipation in VLSI’s

I/O

I/O

clock

clock

memory

clock

I/O

clock

logic

MPU1

MPU1

ASSP1

memory

ASSP2

memory

memory

logic

I/O

logic

MPU1: low-end microprocessor for embedded use

MPU2: high-end CPU with large amount of cache

ASSP1: MPEG2 decoder

ASSP2: ATM switch


Current design issues in lower power problem

Energy-hungry Function by Network Server:

Infopad (univ. of California, Berkeley), weight < 1 pound,

0.5W (reflective color display) + 0.5W (computation,communication, I/O support) = 1W (Alpha chip: 25W StrongARM: 215 MHz at 2.0V:0.3W)

runtime 50 hours, target: 100MIPS/mW.

Deep-sub micron (0.35 - 0.18) with low voltage for portable full motion video terminal; 0:5m : 40 AA NiMH; 1m : 1 AA NiMH

System-On-A-Chip to reduce external Interconnection Capacitances

Power Management: shut down idle units

Power Optimization Techniques in Software, Architecture,Logic/Circuit,

Layout Phases to reduce operations, frequency, capacitance, switching activity with maintaining the same throughput.

Current Design Issues in Lower Power Problem



Road map in semiconductor device integration
Road-Map in Semiconductor Device Integration



Power component

Static: Leakage current(<< 1%)

Dynamic:

Short Circuit power(10-30%): Short circuit ow during transitions,

Switching (or capacitive) power(70-90%): Charging/discharging of capacitive loads during transitions

Power Component


V dd vs delay
Vdd vs Delay

  • use architecture optimization to compensate for slower operation, e.g., Parallel Processing and Pipelining for concurrent increasing and critical path reducing.

  • Scale down device sizes to compensate for delay (Interconnects do not scale proportionately and can become dominant)




2 power management

2. Power Management


Power consumption in multimedia systems

LCD: 54.1%, HDD 16.8%, CPU 10.7%, VGA/VRAM 9.6%, SysLogic 4.5%, DRAM 1.1%, Others: 3.2%

5-55 Mode:

Display mode: CPU is in sleep-mode (55 minutes), LCD (VRAM + LCDC)

CPU mode: Display is idle ( 5 minutes), Looking up - data retrival

Handwrite recognition - biggest power (memory, system bus active)

Power Consumption in Multimedia Systems


Power management

DPM 4.5%, DRAM 1.1%, Others: 3.2%

(Dynamic Power Management): stops the clock switching of a specific unit generated by clock generators. The clock regenerators produce two clocks, C1 and C2 . The logic: 0.3%, 10-20% of power savings.

SPM

(Static Power Management): saving of the power dissipation in the steady mode. When the system (or subsystem) remains idle for a significant period time, then the entire chip

(or subsystem) is shut-down.

Identify power hungry modules and look for opportunities to reduce power

If f is increased, one has to increase the transistor size or Vdd.

Power Management


Power management christian piguet@csemne ch
Power Management([email protected]) 4.5%, DRAM 1.1%, Others: 3.2%

  • use right supply and right frequency to each part of the system If one has to wait on the occurence of some input, only a small circuit could wait and wake-up the main circuit when the input occurs.

  • Another technique is to reduce the basic frequency for tasks that can be executed slowly.

  • PowerPC 603 is a 2-issue (2 instructions read at a time) with 5 parallel

  • execution units. 4 modes:

    • Full on mode for full speed

    • Doze mode in which the execution units are not running

    • Nap mode which also stops the bus clocking and the Sleep mode which stops the clock generator

    • Sleep mode which stops the clock generator with or without the PLL (20-100mW).

  • Superpipelined MIPS R4200 : 5-stage pipleline, MIPS R4400: 8 stage, 2 execution units, f/2 in reduce mode.


TI 4.5%, DRAM 1.1%, Others: 3.2%

  • Two DSPs: TMS320C541, TMS320C542 reduce power and chip count and system cost for wireless communication applications

  • C54X DSPs, 2.7V, 5V, Low-Power Enhanced Architecture DSP (LEAD) family: Three different power down modes, these devices are well-suited for wireless communications products such as digital cellular phones, personal digital assistants, and wireless modem,low power on voice coding and decoding

  • The TMS320LC548 features:

    • 15-ns (66 MIPS) or 20-ns (50 MIPS) instruction cycle times

    • 3.0- and 3.3-V operation

  • 32K 16-bit words of RAM and 2K 16-bit words of boot ROM on-chip

  • Integrated Viterbi accelerator that reduces Viterbi butterfly update in four instruction cycles for GSM channel decoding

  • Powerful single-cycle instructions (dual operand, parallel instructions, conditional instructions)

  • Low-power standby modes


Power estimation techniques
Power Estimation Techniques 4.5%, DRAM 1.1%, Others: 3.2%

  • Circuit Simulation (SPICE): a set of input vectors, accurate, memory and time constraints

  • Monte Carlo: randomly generated input patterns, normal distributed power per time interval T using a simulator switch level simulation (IRSIM): defined as no. of rising and falling transitions over total number of inputs

  • Powermill (transistor level): steady-state transitions, hazards and glitches, transient short circuit current and leakage current; measures current density and voltage drop in the power net and identifies reliability problem caused by EM failures, ground bounce and excessive voltage drops.

  • DesignPower (Synopsys): simulation-based analysis is within 8-15% of SPICE in terms of percentage difference (Probability-based analysis is within 15-20% of SPICE).


Cache memory management
Cache/Memory Management 4.5%, DRAM 1.1%, Others: 3.2%

  • Clock and memory consumes between 15% to 45% of the total power in digital computers

  • As block size increases, the energy required to service miss increases due to increased memory access external-memory access (530 mA) vs. on-chip access(300mA): Replacing excessive accesses to background memory by foreground memory

  • Cache vertical partitioning (buffering): multi-level variable-size caches

    Caches are powerdown when idle.

  • Cache horizontal partitioning (subarray access): several segments can be powered individually. Only the cache sub-bank where the requested data is located consumes power in each cache access.

  • Using distributed memory instead of a single centralized memory

  • Locality of reference to eliminate expensive data transfer across high capacitance busses

  • Cache misses consume more energy (directed-mapping or k-associated mapping?), page faults consume more energy


Power management1

Block Power Management (Sleep, standby mode) Scheme by Enabling Clock

Clock Power Management Scheme by adding Clock Generation block

Power Management


3 architectural level design

3. Enabling ClockArchitectural Level Design


Architectural level synthesis
Architectural-level Synthesis Enabling Clock

  • Translate HDL models into sequencing graphs.

  • Behavioral-level optimization:

    • Optimize abstract models independently from the implementation parameters.

  • Architectural synthesis and optimization:

    • Create macroscopic structure:

      • data-path and control-unit.

    • Consider area and delay information

  • Hardware compilation:

    • Compile HDL model into sequencing graph.

    • Optimize sequencing graph.

    • Generate gate-level interconnection for a cell library. of the implementation.


Power measure of p
Power Measure of Enabling ClockP


System level solutions

Spatial locality Enabling Clock: an algorithm can be partitioned into natural clusters based on connectivity

Temporal locality: average lifetimes of variables (less temporal storage, probability of future accesses referenced in the recent past).

Precompute physical capacitance of Interconnect and switching activity (number of bus accesses)

Architecture-Driven Voltage Scaling: Choose more parallel architecture

Supply Voltage Scaling : Lowering V dd reduces energy, but increase delays

System-Level Solutions


Software power issues
Software Power Issues Enabling Clock

Upto 40% of the on-chip power is dissipated on the buses !

  • System Software : OS, BIOS, Compilers

  • Software can affect energy consumption at various levels Inter-Instruction Effects

  • Energy cost of instruction varies depending on previous instruction

  • For example, XORBX 1; ADDAX DX;

  • Iest = (319:2+313:6)=2 = 316:4mA Iobs =323:2mA

  • The difference defined as circuit state overhead

  • Need to specify overhead as a function of pairs of instructions

  • Due to pipeline stalls, cache misses

  • Instruction reordering to improve cache hit ratio


Avoiding wastful computation
Avoiding Wastful Computation Enabling Clock

  • Preservation of data correlation

  • Distributed computing / locality of reference

  • Application-specific processing

  • Demand-driven operation

  • Bus-Inverted Coding

  • Transformation for memory size reduction

    • Consider arrays A and C are already available in memory

    • When A is consumed another array B is generated; when C is consumed a scalar value D is produced.

    • Memory Size can be reduced by executing the j loop before the i loop so that C is consumed before B is generated and the same memory space can be used for both arrays.



Architecture lower power design
Architecture Lower Power Design Enabling Clock

  • Optimum Supply Voltage Architecture through Hardware Duplication (Trading Area for Lower Power) and/or Pipelining

    • complex and fewer instruction requires less encoding, but larger decode logic!

  • Use small complex instruction with smaller instruction length (e.g., Hitachi SH: 16-bit fixed-length, arithmetic instruction uses only two operands, NEC V800: variable-length instruction decoding overhead )

  • Superscalar: CPI < 1: parallel instruction execution. VLIW architecture.


Variable supply voltage block diagram

Computational work varies with time. An approach to reduce the energy consumption of such systems beyond shut down involves the dynamic adjustment of supply voltage based on computational workload.

The basic idea is to lower power supply when the a fixed supply for some fraction of time.

The supply voltage and clock rate are increased during high workload period.

Variable Supply Voltage Block Diagram


Power reduction using variable supply
Power Reduction using Variable Supply the energy consumption of such systems beyond shut down involves

  • Circuits with a fixed supply voltage work at a fixed speed and idle if the data sample requires less than the

  • maximum amount of computation. Power is reduced in a linear fashion since the energy per operation is fixed.

  • If the work load for a given sample period is less than peak, then the delay of the processing element can be increased by a factor of 1/workload without loss in throughput, allowing the processor to operate at a lower supply voltage. Thus, energy per operation varies.


Data driven signal processing
Data Driven Signal Processing the energy consumption of such systems beyond shut down involves

The basic idea of averaging two samples are buffered and their work loads are averaged.

The averaged workload is then used as the effective workload to drive the power supply.

Using a pingpong buffering scheme, data samples In +2, In +3

are being buffered while In, In +1

are being processed.


Architecture of microcoded instruction set processor
Architecture of Microcoded Instruction Set Processor the energy consumption of such systems beyond shut down involves


Power and area
Power and Area the energy consumption of such systems beyond shut down involves

1.5V and 10MHz clock rate: instruction and data memory accesses account for 47% of the total power consumption.


Datapath parallelization
Datapath Parallelization the energy consumption of such systems beyond shut down involves


Memory parallelization
Memory Parallelization the energy consumption of such systems beyond shut down involves

At first order P= C * f/2 * Vdd2


Pipelined micro p
Pipelined Micro-P the energy consumption of such systems beyond shut down involves


Architecture trade off
Architecture Trade-Off the energy consumption of such systems beyond shut down involves

Ppipeline =

(1.15C)( 0.58V)2 (f)

= 0.39P

NON-PIPLELINED Implementation

Pparallel =

(2.15C)(0.58V)2 (0.5f)

= 0.36P

PIPLELINED Implementation


Through wave pipelining
Through WAVE PIPELINING the energy consumption of such systems beyond shut down involves


Different classes of risc micro p
Different Classes of RISC Micro-P the energy consumption of such systems beyond shut down involves


Application specific coprocessor
Application Specific Coprocessor the energy consumption of such systems beyond shut down involves

  • DSP's are increasingly called upon to perform tasks for which they are not ideally suited, for example, Viterbi decoding.

  • They may also take considerably more energy than a custom solution.

  • Use the DSP for portions of algorithms for which it is well suited, and craft an application-specic coprocessor (i.e., custom hardware) for other tasks.

  • This is an example of the difference between power and energy

  • The application-specific coprocessor may actually consume a more power than the DSP, but it may be able to accomplish the same task in far less time, resulting in a net energy savings.

  • Power consumption varies dramatically with the instruction being executed.


Clock per instruction cpi
Clock per Instruction (CPI) the energy consumption of such systems beyond shut down involves


Superpipeline micro p
SUPERPIPELINE micro-P the energy consumption of such systems beyond shut down involves


Vliw architecture
VLIW Architecture the energy consumption of such systems beyond shut down involves

Compiler takes the responsibility for finding the operations that can be issued in parallel and creating a single very long instruction containing these operations. VLIW instruction decoding is easier than superscalar instruction due to the fixed format and to no instruction dependency.

The fixed format could present more limitations to the combination of operations.

Intel P6: CISC instructions are combined on chip to provide a set of micro-operations (i.e., long instruction word) that can be executed in parallel.

As power becomes a major issue in the design of fast -Pro, the simple is the better architecture.

VLIW architecture, as they are simpler than N-issue machines, could be considered as promising architectures to achieve simultaneously

high-speed and low-power.


Synchronous vs asynchronous systems
Synchronous VS. Asynchronous SYSTEMS the energy consumption of such systems beyond shut down involves

  • Synchronous system: A signal path starts from a clocked flip- flop through combinational gates and ends at another clocked flip- flop. The clock signals do not participate in computation but are required for synchronizing purposes. With advancement in technology, the systems tend to get bigger and bigger, and as a result the delay on the clock wires can no longer be ignored. The problem of clock skew is thus becoming a bottleneck for many system designers. Many gates switch unnecessarily just because they are connected to the clock, and not because they have to process new inputs. The biggest gate is the clock driver itself which must switch.

  • Asynchronous system (self-timed): an input signal (request) starts the computation on a module and an output signal (acknowledge) signifies the completion of the computation and the availability of the requested data. Asynchronous systems are potentially response to transitions on any of their inputs at anytime, since they have no clock with which to sample their inputs.


Asynchronous systems
Asynchronous SYSTEMS the energy consumption of such systems beyond shut down involves

  • More difficult to implement, requiring explicit synchronization between communication blocks without clocks

  • If the signal feeds directly to conventional gate-level circuitry, invalid logic levels could propagate throughout the system.

  • Glitches, which are filtered out by the clock in synchronous designs, may cause an asynchronous design to malfunction.

  • Asynchronous designs are not widely used, designers can't find the supporting design tools and methodologies they need.

  • DCC Error Corrector of Compact cassette player saves power of 80% as compared to the synchronous counterpart.

  • Offers more architectural options/freedom encourages distributed, localized control offers more freedom to adapt the supply voltage


Asynchronous modules
Asynchronous Modules the energy consumption of such systems beyond shut down involves


Example abcs protocol

6% the energy consumption of such systems beyond shut down involves more logics

Example: ABCS protocol


Control synthesis flow
Control Synthesis Flow the energy consumption of such systems beyond shut down involves


Pipelined self timed micro p
PIPELINED SELF-TIMED micro P the energy consumption of such systems beyond shut down involves


Programming style
Programming Style the energy consumption of such systems beyond shut down involves


Speed vs power optimization
Speed vs. Power Optimization the energy consumption of such systems beyond shut down involves


Von neumann versus harvard
VON NEUMANN VERSUS HARVARD the energy consumption of such systems beyond shut down involves


Low vdd main memories
Low Vdd Main Memories the energy consumption of such systems beyond shut down involves


Cache memories
CACHE MEMORIES the energy consumption of such systems beyond shut down involves


Low power memory
Low Power Memory the energy consumption of such systems beyond shut down involves

  • Hierarchical Word Line: Divide the memory in different blocks and access the bit cells of the desired block

  • Selective precharge: Many bit lines are discharged even when these locations are not accessed. Only bit lines which will be accesses are precharged.

  • Minimization of Non-zero Terms in the ROM table: Zero terms do not switch bit lines and reduce capacitance in both bit lines and row lines.

    • Inverted ROM: If the number of ones is very high, the whole ROM core can be inverted.

    • Inverted Row: A given row is inverted if more than half of the bits are non-zero terms. An extra bit is required to perfoem encoding.

    • Sign magnitude representation: ROM is used to store the coefficients of a digital filter. As a result, a significant amount of the non-zero terms are due to the sign extension of the negative coefficients. The main drawback of this type is that a conversion to two’s complement is required at the end of a cycle, which slows down the ROM.

    • Sign magnitude and inverted block:

  • Difference Encoding: reduce the size of the ROM core. If the value between adjacent data do not change significantly, the ROM core stores the difference between the data.


Low power memory1
Low Power Memory the energy consumption of such systems beyond shut down involves

  • Smaller ROMS: in 102 tap filter, more than 70% of the coefficients are below 18 bits. Still the largest coefficients are below 18 bits. Still the largest coefficient goes up 24 bits. A better implementation can be achieved if the large coefficients are stored in a wide ROM with fewer address; the small coefficients are stored in narrow ROM with many addresses. A similar approach is applied for locations in ROM which are often accessed. Loations that are accesses frequently are stored in a small, fast ROM, while the other locations are stored in a larger ROM.

  • NMOS precharge: bit lines are precharged to Vdd - Vt. A drawback of this technique is degradation of noise margins and the body bias effect.

  • Buffer Sizing: a large set of buffers is required in the control logic to drive the address lines through the decoder, generate the contol signals for the column multiplexers, drive the row lines and drive the precharge signals.

  • Voltage scaling:


Memory architecture
Memory Architecture the energy consumption of such systems beyond shut down involves


Exploiting locality for low power design
Exploiting Locality for Low-Power Design the energy consumption of such systems beyond shut down involves

  • A spatially local cluster: group of algorithm operations that are tightly

  • connected to each other in the flow graph representation.

  • Two nodes are tightly connected to each other on the flow graph representation

  • if the shortest distance between them, in terms of number of edges traversed, is low.

  • Power consumption (mW) in the maximally time-shared and fully-parallel versions of the QMF sub-band coder filter

  • Improvement of a factor of 10.5 at the expense of a 20% increase in area

  • The interconnect elements (buses, multiplexers, and buffers) consumes 43% and 28% of the total power in

  • the time-shared and parallel versions.


Cascade filter layouts
Cascade filter layouts the energy consumption of such systems beyond shut down involves

(a)Non-local implementation from Hyper (b)Local implementation from Hyper-LP


Stage skip pipeline
Stage-Skip Pipeline the energy consumption of such systems beyond shut down involves

  • The power savings is achieved by stopping the instruction fetch and decode stages of the processor during

  • the loop execution except its first iteration.

  • DIB = Decoded Instruction Buffer

  • 40 % power savings using DSP or RISC processor.


Stage skip pipeline1
Stage-Skip Pipeline the energy consumption of such systems beyond shut down involves

  • Selector: selects the output from either the instruction decoder or DIB

  • The decoded instruction signals for a loop are temporarily stored in the DIB and are reused in each iteration of the loop.

  • The power wasted in the conventional pipeline is saved in our pipeline by stopping the instruction fetching and decoding for each loop execution.


Stage skip pipeline2
Stage-Skip Pipeline the energy consumption of such systems beyond shut down involves

Majority of execution cycles in signal processing programs are used for loop execution :

40% reduction in power with area increase 2%.


Parallel lifo scenario
Parallel LIFO Scenario the energy consumption of such systems beyond shut down involves


Parallel serial converter
Parallel-serial Converter the energy consumption of such systems beyond shut down involves


D flip flop parallelization
D- flip- flop Parallelization the energy consumption of such systems beyond shut down involves


State machine
State Machine the energy consumption of such systems beyond shut down involves


Frequency multipliers and dividers
Frequency Multipliers and Dividers the energy consumption of such systems beyond shut down involves


Data reuse exploration
Data Reuse Exploration the energy consumption of such systems beyond shut down involves

  • MH(memory hierarchy) introduces copies of data from larger to smaller memories in DFG.

  • Power consumption is decreased because data is now read mostly from smaller memories, while it is increased because extra memory transfers are introduced.

  • Moreover, adding another layer of hierarchy has a negative effect on the area and interconnect cost.


State instruction encoding

Architecture of Control Logic in Microprocessor the energy consumption of such systems beyond shut down involves

State Transition Diagram

Binary Code Mapping

Hardware Implementation

State/Instruction Encoding

If e has higher switching prob. (e.g., S0 =branch, S1=compare), then encode S0 and S1 with gray code style.


Optimizing power using transformation
Optimizing Power the energy consumption of such systems beyond shut down involves using Transformation


Summary of results
Summary of Results the energy consumption of such systems beyond shut down involves

Optimum voltage for low-power is around 1.5V


Data flow based transformations
Data- flow based transformations the energy consumption of such systems beyond shut down involves

  • Tree Height reduction.

  • Constant and variable propagation.

  • Common subexpression elimination.

  • Code motion

  • Dead-code elimination

  • The application of algebraic laws such as commutability, distributivity and associativity.

  • Most of the parallelism in an algorithm is embodied in the loops.

  • Loop jamming, partial and complete loop unrolling, strength reduction and loop retiming and software pipelining.

  • Retiming: maximize the resource utilization.


Tree height reduction
Tree-height reduction the energy consumption of such systems beyond shut down involves

  • Example of tree-height reduction using commutativity and associativity

  • Example of tree-height reduction with distributivity


Sub expression elimination
Sub-expression elimination the energy consumption of such systems beyond shut down involves

  • Logic expressions:

    • Performed by logic optimization.

    • Kernel-based methods.

  • Arithmetic expressions:

    • Search isomorphic patterns in the parse trees.

    • Example:

    • a= x+ y; b = a+ 1; c = x+ y;

    • a= x+ y; b = a+ 1; c = a;


Examples of other transformations
Examples of other transformations the energy consumption of such systems beyond shut down involves

  • Dead-code elimination:

    • a= x; b = x+ 1; c = 2 * x;

    • a= x; can be removed if not referenced.

  • Operator-strength reduction:

    • a= x2 ; b = 3 * x;

    • a= x * x; t = x<<1; b = x+ t;

  • Code motion:

    • for ( i = 1; i < a * b) { }

    • t = a * b; for ( i = 1; i < t) { }


Strength reduction
Strength reduction the energy consumption of such systems beyond shut down involves


Strength reduction1
Strength Reduction the energy consumption of such systems beyond shut down involves


Control flow based transformations
Control- flow based transformations the energy consumption of such systems beyond shut down involves

  • Conditional expansion

    • Transform conditional into parallel execution with test at the end.

    • Useful when test depends on late signals.

    • May preclude hardware sharing.

    • Always useful for logic expressions.

    • Example:

    • y= ab; if ( a) x= b+d; else x= bd; can be expanded to: x= a( b+ d) + a’bd;

    • y= ab; x= y+ d( a+ b);

  • Model expansion.

    • Expand subroutine flatten hierarchy.

    • Useful to expand scope of other optimization techniques.

    • Problematic when routine is called more than once.

    • Example:

    • x= a+ b; y= a * b; z = foo( x, y) ;

    • foo( p, q) {t =q-p; return(t);}

    • By expanding foo:

    • x= a+ b; y= a * b; z = y-x;


Pipelining
Pipelining the energy consumption of such systems beyond shut down involves


Associativity transformation
Associativity Transformation the energy consumption of such systems beyond shut down involves


Fir parallelization
FIR Parallelization the energy consumption of such systems beyond shut down involves


Fir parallelization1
FIR PARALLELIZATION the energy consumption of such systems beyond shut down involves


Fir filter parallelization
FIR Filter Parallelization the energy consumption of such systems beyond shut down involves


Fir parallelization two working phases
FIR parallelization: two working phases the energy consumption of such systems beyond shut down involves


Iir filter recursive function
IIR filter recursive function the energy consumption of such systems beyond shut down involves


Recursive function
Recursive Function the energy consumption of such systems beyond shut down involves


Interlaced accumulation programming for low power
Interlaced Accumulation Programming for Low the energy consumption of such systems beyond shut down involves Power


4 register transfer level design

4. the energy consumption of such systems beyond shut down involves Register Transfer Level Design


Fir3 block diagram and flow graph
FIR3 Block Diagram and Flow Graph the energy consumption of such systems beyond shut down involves


High level power estimation
High-Level Power Estimation the energy consumption of such systems beyond shut down involves

  • Pcore = PDP + PMEM + PCNTR + PPROC

  • PDP = PREG +PMUX +PFU + +PFU, where PREG is the power of the registers

  • PMUX is the power of multiplexers

  • PFU is the power of functional units

  • PINT is the power of physical interconnet capacitance


High level power estimation p reg
High-Level Power Estimation: P the energy consumption of such systems beyond shut down involves REG

  • Compute the lifetimes of all the variables in the given VHDL code.

  • Represent the lifetime of each variable as a vertical line from statement i through statement i + n in the column j reserved for the corresponding varibale v j .

  • Determine the maximum number N of overlapping lifetimes computing the maximum number of vertical lines intersecting with any horizontal cut-line.

  • Estimate the minimal number of N of set of registers necessary to implement the code by using register sharing. Register sharing has to be applied whenever a group of variables, with the same bit-width b i .

  • Select a possible mapping of variables into registers by using register sharing

  • Compute the number w i of write to the variables mapped to the same set of registers. Estimate n i of each set of register dividing w i by the number of statements S: i =wi/S; hence TR imax = n i f clk .

  • Power of latches and flip flops is consumed not only during output transitions, but also during all clock edges by the internal clock buffers

  • The non-switching power PNSK dissipated by internal clock buffers accounts for 30% of the average power for the 0.38-micron and 3.3 V operating system.

  • In total,


P cntr
P the energy consumption of such systems beyond shut down involves CNTR

  • After scheduling, the control is defined and optimized by the hardware mapper and

    further by the logic synthesis process before mapping to layout.

  • Like interconnect, therefore, the control needs to be estimated statistically.

  • Global control model:

Local control model: the local controller account for a larger percentage of the total capacitance than the global controller.

Where Ntrans is the number of tansitions, nstates is the number of states, Bf is the bus factor, and Clc is the capacitance switched in any local controller in one sample period. Bf is the ratio of the number of bus accesses to the number of busses.


N trans
N the energy consumption of such systems beyond shut down involves trans

  • The number of transitions depends on assignment, scheduling, optimizations, logic

  • optimization, the standard cell library used, the amount of glitchings and the statistics of the inputs.


Behavioral synthesis
Behavioral Synthesis the energy consumption of such systems beyond shut down involves

  • loop unrolling : localize the data to reduce the activity of the inputs of the functional units or two output samples are computed in parallel based on two input samples.

Neither the capacitance switched nor the voltage is altered. However, loop unrolling enables several other transformations (distributivity, constant propagation, and pipelining). After distributivity and constant propagation,

  • The transformation yields critical path of 3, thus voltage can be dropped.

  • Clock Selection : Choose optimal system clock period Eliminate slacks/improve resource utilization and Enable greater voltage scaling

  • Module selection : For each operation, choose library template

  • Flow graph restructuring : pull out operations on the critical cycle.


High level power estimation p mux and p fu
High-Level Power Estimation: P the energy consumption of such systems beyond shut down involves MUX and PFU


Critical path

Longest delayed path from input to output in combinational logic

Determine operating clock frequency

Resizing non-critical path transistor (In-Place Optimization)

Critical path in Synchronous Sequential logic

Critical Path



Retiming
Retiming logic

Flip- flop insertion to minimize hazard activity moving a flip- flop in a circuit


Exploiting spatial locality for interconnect power reduction
Exploiting spatial locality for interconnect logicpower reduction

Global

Local

Adder1

Adder2


Balancing maximal time sharing and fully parallel implementation
Balancing maximal time-sharing and logicfully-parallel implementation

A fourth-order parallel-form

IIR filter

(a) Local assignment

(2 global transfers),

(b) Non-local assignment

(20 global transfers)




Hazard propagation elimination by clocked sampling
Hazard propagation elimination by clocked sampling logic

By sampling a steady state signal at a register input,

no more glitches are propagated through the next

combinational logics.




Regularity
Regularity logic

  • Common patterns enable the design of less complex architecture and therefore simpler interconnect structure (muxes, buffers, and buses). Regular designs often have less control hardware.


Module selection
Module Selection logic

  • Select the clock period, choose proper hardware modules for all operations(e.g., Wallace or Booth Multiplier), determine where to pipeline (or where to put registers), such that a minimal hardware cost is obtained under given timing and throughput constraints.

  • Full pipelining: ineffective clock period mismatches between the execution times of the operators. performing operations in sequence without immediate buffering can result in a reduction of the critical path.

  • Clustering operations into non-pipelining hardware modules, the reusability of these modules over the complete computational graph be maximized.

  • During clustering, more expensive but faster hardware may be swapped in for operations on the critical path if the clustering violates timing constraints


Estimation
Estimation logic

  • Estimate min and max bounds on the required resources to

    • delimit the design space min bounds to serve as an initial solution

    • serve as entries in a resource utilization table which guides the transformation, assignment and scheduling operations

  • Max bound on execution time is tmax: topological ordering of DFG using ASAP and ALAP

  • Minimum bounds on the number of resources for each resource class

Where NRi: the number of resources of class Ri

dRi : the duration of a single operation

ORi : the number of operations


Exploring the design space
Exploring logicthe Design Space

  • Find the minimal area solution constrained to the timing constraints

  • By checking the critical paths, it determine if the proposed graph violates the timing constraints. If so, retiming, pipelining and tree height reduction can be applied.

  • After acceptable graph is obtained, the resource allocation process is

  • initiated.

    • change the available hardware (FU's, registers, busses)

    • redistribute the time allocation over the sub-graphs

    • transform the graph to reduce the hardware requirements.

  • Use a rejectionless probabilistic iterative search technique (a variant of Simulated Annealing), where moves are always accepted. This approach reduces computational complexity and gives faster convergence.



Scheduling and binding
Scheduling and Binding logic

  • The scheduling task selects the control step, in which a given operation will happen, i.e., assign each operation to an execution cycle

  • Sharing: Bind a resource to more than one operation.

    • Operations must not execute concurrently.

  • Graph scheduled hierachically in a bottom-up fashion

  • Power tradeoffs

    • Shorter schedules enable supply voltage (Vdd) scaling

    • Schedule directly impacts resource sharing

    • Energy consumption depends what the previous instruction was

    • Reordering to minimize the switching on the control path

  • Clock selection

    • Eliminate slacks

    • Choose optimal system clock period


Asap scheduling

Algorithm logic

HAL Example

ASAP Scheduling


Algorithm logic

ALAP Scheduling

  • HAL Example


Force directed scheduling
Force Directed Scheduling logic

  • Used as priority function.

  • Force is related to concurrency.

  • Sort operations for least force.

  • Mechanical analogy:

    • Force = constant displacement.

    • constant = operation-type distribution.

    • displacement = change in probability.




Force directed scheduling2
Force-Directed Scheduling logic

  • Algorithm (Paulin)


Force directed scheduling example

Probability of scheduling operations into control steps logic

Probability of scheduling operations into control steps after operation o3 is scheduled to step s2

Force-Directed Scheduling Example

  • Operator cost for multiplications in a

  • Operator cost for multiplications in c


List scheduling

The scheduled DFG logic

DFG with mobility labeling (inside <>)

ready operation list/resource constraint

List Scheduling


Static list scheduling

DFG logic

Partial schedule of five nodes

Priority list

Static-List Scheduling

The final schedule


Loop folding
Loop folding logic

  • Reduce execution delay of a loop.

  • Pipeline operations inside a loop.

    • Overlap execution of operations.

    • Need a prologue and epilogue.

  • Use pipeline scheduling for loop graph model.


Dfg restructuring

DFG2 logic

DFG2 after redundant operation insertion

DFG Restructuring



Control synthesis
Control Synthesis Scheduling

  • Synthesize circuit that:

  • Executes scheduled operations.

  • Provides synchronization.

  • Supports:

    • Iteration.

    • Branching.

    • Hierarchy.

    • Interfaces.


Allocation
Allocation Scheduling

  • Bind a resource to more than one operation.


Optimum binding
Optimum binding Scheduling


Example
Example Scheduling


Resource sharing
RESOURCE SHARING Scheduling

  • Parallel vs. time-sharing buses (or execution units)

  • Resource sharing can destroy signal correlations and increase switching activity, should be done between operations that are strongly connected.

  • Map operations with correlated input signals to the same units

  • Regularity: repeated patterns of computation (e.g., (+, * ), ( * ,*), (+,>)) simplifying interconnect (busses, multiplexers, buffers)


Datapath interconnections

Multiplexer-oriented datapath Scheduling

Bus-oriented datapath

Datapath interconnections


Sequential execution
Sequential Execution Scheduling

  • Example of three micro-operations in the same clock period


Insertion of latch out
Insertion of Latch (out) Scheduling

  • Insertion of latches at the output ports of the functional units


Insertion of latch in out
Insertion of Latch (in/out) Scheduling

  • Insertion of latches at both the input and output ports of the functional units


Overlapping data transfer in
Overlapping Data Transfer(in) Scheduling

  • Overlapping read and write data transfers


Overlapping of data transfer in out
Overlapping of Data Transfer (in/out) Scheduling

  • Overlapping data transfer with functional-unit execution


Register allocation using clique partitioning

Scheduled DFG Scheduling

Graph model

Lifetime intervals of variable

Clique-partitioning solution

Register Allocation Using Clique Partitioning


Left edge algorithm
Left-Edge Algorithm Scheduling

  • Register allocation using Left-Edge Algorithm


Register allocation left edge algorithm

Sorted variable lifetime intervals Scheduling

Five-register allocation result

Register Allocation: Left-Edge Algorithm


Register allocation
Register Allocation Scheduling

  • Allocation : bind registers and functional modules to variables and operations in the CDFG and specify the interconnection among modules and registers in terms of MUX or BUS.

  • Reduce capacitance during allocation by minimizing the number of functional modules, registers, and multiplexers.

  • Composite weight w.r.t transition activity and capacitance loads is incorporated into CDFG.

  • Find the highest composite weight and merge the two nodes it joins, i.e., maps the corresponding variable to the same register.

  • Allocation continues till no edges are left in the CDFG while updating the composite weight values.

  • Set the maximum # of operations alive in any control step to be one.

  • Sequence operations/variables to enhance signal correlations


Exploiting spatial locality for interconnect power reduction1
Exploiting spatial locality for Scheduling interconnect power reduction

  • A spatially local cluster: group of algorithm operations that are tightly connected to each other in the flowgraph representation.

  • Two nodes are tightly connected to each other on the flowgraph representaion if the shortest distance between them, in terms of number of edges traversed, is low.

  • A spatially local assignment is a mapping of the algorithm operations to specific hardware units such that no operations in different clusters share the same hardware.

  • Partitioning the algorithm into spatially local clusters ensures that the majority of the data transfers take place within clusters (with local bus) and relatively few occur between clusters (with global bus).

  • The partitioning information is passed to the architecture netlist and floorplanning tools.

  • Local: A given adder outputs data to its own inputs Global: A given adder outputs data to the aother adder's inputs


Hardware mapping
Hardware Mapping Scheduling

  • The last step in the synthesis process maps the allocated, assigned and scheduled flow graph (called the decorated flow graph) onto the available hardware blocks.

  • The result of this process is a structural description of the processor architecture, (e.g., sdl input to the Lager IV silicon assembly environment).

  • The mapping process transforms the flow graph into three structural sub-graphs:

    the data path structure graph

    the controller state machine graph

    the interface graph (between data path control inputs and the

    controller output signals)


Spectral partitioning in high level synthesis
Spectral Partitioning in High-Level Synthesis Scheduling

  • The eigenvector placement obtained forms an ordering in which nodes tightly connected to each other are placed close together.

  • The relative distances is a measure of the tightness of connections.

  • Use the eigenvector ordering to generate several partitioning solutions

  • The area estimates are based on distribution graphs.

  • A distribution graph displays the expected number of operations executed in each time slot.

  • Local bus power: the number of global data transfers times the area of the cluster

  • Global bus power: the number of global data transfer times the total area:



Interconnection estimation
Interconnection Estimation Scheduling

  • For connection within a datapath (over-the-cell routing), routing between units increases the actual height of the datapath by approximately 20-30% and that most wire lengths are about 30-40% of the datapath height.

  • Average global bus length : square root of the estimated chip area.

  • The three terms represent white space, active area of the components, and wiring area. The coefficients are derived statistically.


Experiments
Experiments Scheduling


Datapath generation
Datapath Generation Scheduling

  • Register file recognition and the multiplexer reduction:

    • Individual registers are merged as much as possible into register files

    • reduces the number of bus multiplexers, the overall number of busses (since all registers in a file share the input and output busses) and the number of control signals (since a register file uses a local decoder).

  • Minimize the multiplexer and I/O bus, simultaneously (clique partitioning is Np-complete, thus Simulated Annealing is used)

  • Data path partitioning is to optimize the processor floorplan

  • The core idea is to grow pairs of as large as possible isomorphic regions from corresponding of seed nodes.


Hardware mapper
Hardware Mapper Scheduling


Test example
Test Example Scheduling




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