Final_project

FINAL PROJECT PRESENTATIONSubmitted by

Pranav S Devalla829-844-527

Literary Review

on Energy- and

Thermal- aware

task allocation

on SoCs

Abstract

0 The aggressive semiconductor technology scaling has been pushing the device feature size into the deep sub-micron region.

0 As a result, the chip power density has been doubled every two to three years.

0 This increased power has directly translated into high temperature, which negatively affects a system's cost, performance and reliability.

0 In this review, various methodologies for thermal and energy problem mitigation are presented and compared

Power Consumption Issues0 Stress on batteries in portable devices such as laptops and phones

0 Can be minimized through voltage and frequency scaling

0 High temperature greatly shortens the lifespan of a processor 0 100C increase in temperature reduces component life by 50% [1]

0 Obvious approach is to use bigger heat sinks and air- cooling techniques (for desktop and laptop computers)0 Expensive and inefficient

0 Power- aware techniques are not efficient in handling these issues0 Logic blocks within the chip have different power densities (e.g. due to

different levels of switching activity) 0 The thermal map of a chip often shows wide variations in temperature0 Many low-power techniques have insufficient impact because they do not

directly target the spatial and temporal behavior of the operating temperature.

Thermal- aware Computing [2]

0 Components of power consumption0 Dynamic

0 consumed when devices switch from one logic level to another.0 related to the level of computational (switching) activity

0 Leakage0 power that flows from source to ground whenever a device is powered up0 grows exponentially with temperature

0 Thermal modeling0 Hotspot Heatflow model [3]

Thermal- aware Computing

0 Thermal- aware chip design (Static)0 focus on the floorplanning phase of the physical design process [4,5,6,7]

0 Floorplanning algorithms can be modified to also include reducing the maximum temperature of a block in the chip.

0 Migration Computing [8]0 Increasing silicon area allocated to hotblocks [9]

0 Runtime Thermal Management (Dynamic)0 The operating system controls the scheduling of tasks and also assign tasks to

individual cores0 Heat Balancing0 Heat Unbalancing0 Reducing Execution Rate of Hot Tasks0 Adding a Predictive Component

Thermal- aware Computing

Runtime Techniques Methodology

Voltage Scaling Change voltage levels to adjust power and energy

consumption. Clock rates are reduced to match the

increased circuit delay that results

Heat Balancing Spreads the thermal load among multiple cores to

approximately even out their temperatures.

Heat Unbalancing Reduce thermal cycling effects: accept significant

temperature differentials between the cores as long as

specified temperature levels are not breached.

Throttling Reduce the rate at which heat is generated byreducing instruction fetch rate and similar

parameters.

Thermal- aware Scheduling

0 Thermal aware task allocation in SoCs

0 Dynamic Thermal Management through Task-Scheduling [18]0 Thermal-Aware Task Allocation and Scheduling for Embedded Systems [19]0 Static and Dynamic Temperature-Aware Scheduling for Multiprocessor SoCs

[20]

Thermal-Aware Task Allocation and Scheduling for Embedded Systems (Hung

et. al)

0 Proposed an algorithm that is used as a subroutine for hardware/software co-synthesis0 To exploit resource sharing

0 Traditional algorithms do not take the temperature and power variables into consideration

0 Power awareness0 Dynamic Criticality (DC)

0 Analogous to priority

0

Thermal-Aware Task Allocation and Scheduling for Embedded Systems (Hung

et. al)0 The flows of the thermal-aware co-synthesis framework and thermal-aware platform-based system design

0 The temperature comparisons of the power-aware and the thermal-aware approaches on co-synthesis architecture.

Static and Dynamic Temperature-Aware Scheduling for Multiprocessor SoCs (Coskun et. Al)

0 This looks at Multiprocessor SoCs

0 ILPs to generate static solutions 0 target thermal hotspots and gradients 0 better thermal profile than other static methods

0 Dynamic Scheduling (OS- level scheduling)0 Adaptive –random technique

Static and Dynamic Temperature-Aware Scheduling for Multiprocessor SoCs (Coskun et. Al)

Dynamic Thermal Management through Task-Scheduling (Yang et.

al)0 ThreshHot Algorithm

0 reduces the number of hardware DTMs (Dynamic thermal management) required.

0 Increase in CPU throughput

Dynamic Thermal Management through Task-Scheduling (Yang et.

al)

Comparative TableAuthors Methodology Static Thermal

ManagementDynamic thermal

Management

Static Energy Management

Dynamic Energy

Management

Issues

Hung et. al Implemented algorithm with

temperature and power

vaiables

No Yes No Yes Floorplanning is not effective to

control the lateral heat

transfer. Overhead due to dynamic nature

Coskun et. al Implemented adaptive –

random scheduling algorithm

Yes Yes No Yes Overhead associated with

dynamic awareness is

high

Yang et. al Implemented ThresHot

scheduling algorithm

No Yes No Yes Overhead associated with

dynamic awareness is

high

Energy- aware Computing

0 Energy consumption is a critical measure for battery powered and tethered devices.

0 Energy can be reduced by0 Static 0 Dynamic

0 DVFS

0 Examples0 idle functional units can be powered down [10]0 clock gating [11]0 low-power design [12]0 low-power synthesis [13]0 lower the operating voltage level during the design/synthesis phase [14]

Energy- aware Computing

0 Energy- aware task scheduling 0 EDF [16]0 RM [17]0 LEDF

0 Energy- aware task scheduling in SoCs

0 Energy-Aware Task Allocation for Rate Monotonic Scheduling [21]0 Real-time task scheduling for energy-aware embedded systems [22]0 Energy-Aware Runtime Scheduling for Embedded Multiprocessor SOCs [23]

Energy-Aware Task Allocation for Rate Monotonic Scheduling

(AlEnawy et. al)0 adopt partitioned scheduling and assume that tasks are assigned static

(rate-monotonic) priorities.

0 study and evaluate a number of well-known partitioning heuristics, RMS admission control algorithms, and speed assignment schemes in terms of the feasibility performance and overall energy consumption.

0 Off-line and on-line partitioning

Energy-Aware Task Allocation for Rate Monotonic Scheduling

(AlEnawy et. al)

Real-time task scheduling for energy-aware embedded systems

(Swaminathan et. al)0 Two on-line scheduling algorithms that attempt to

minimize the energy consumed by a periodic task set

0 Both using EDF

0 LEDF

0 E- LEDF

Real-time task scheduling for energy-aware embedded systems

(Swaminathan et. al)

Energy-Aware Runtime Scheduling for Embedded Multiprocessor SOCs (Yang et.

al)

0 Preorder the concurrent behavior as much as possible

0 This task-scheduling method for embedded systems combines the low runtime complexity of a design-time scheduling phase with the flexibility of a runtime scheduling phase.

0 increases design flexibility and reduces design time for multiprocessor SOCs

Energy-Aware Runtime Scheduling for Embedded Multiprocessor SOCs (Yang et.

al)

Comparative Table

Authors Methodology Static Energy Management

Dynamic Energy Management

Issues

AlEnawy et. al Partitioned task scheduling with static priorities

Yes Yes Does not have good performance for on-line

partitioning and overhead due to

dynamic computations

Swaminathan et. al Implemented on-line scheduling

algorithms based on EDF

No Yes Difficulty with Aperiodic and sporadic tasks

and overhead due to dynamic

computations

Yang et. al Algorithm combines the low runtime complexity of a

design-time scheduling phase

with the flexibility of a runtime scheduling

phase.

No Yes Ineffective for very heavy loads and

difficult to implement for

practical applications

Conclusions

0 Thermal management techniques always outperform the energy management techniques

0 Not every technique is easily implementable for practical applications

0 Runtime techniques offer control at a fine level of granularity, but have an overhead associated with them

0 A lot of research in this field of study

Thank You !