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Architecting Embedded Microsystems

Architecting Embedded Microsystems. Building smart, adaptive and efficient systems for networked applications Rajesh K. Gupta Department of Computer Science and Engg. University of California, San Diego http://www-cse.ucsd.edu/~gupta. Graphics Controller. Cellphone Baseband.

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Architecting Embedded Microsystems

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  1. Architecting Embedded Microsystems Building smart, adaptive and efficient systems for networked applications Rajesh K. Gupta Department of Computer Science and Engg. University of California, San Diego http://www-cse.ucsd.edu/~gupta

  2. Graphics Controller Cellphone Baseband Semiconductor “System Chips” • Trend 1: Process technology migration to CMOS • relentless digitization of signals and systems • Trend 2: increasing use of “embedded intelligence” • variety of (multiple) compute engines available on-chip • Trend 3: Networking of embedded intelligence • multiple comm. front-ends, networking available on-chip • The consequence: • smart “spaces”, intelligent interfaces, sensor networks • Integrated circuit chips are driving capability increases with cost reductions.

  3. “Real” Component “Virtual” Component Integrated Circuit & System Design Board-on-chip does not work! • Silicon systems engineering: needs a framework for architectural design, subsystem tradeoffs

  4. SOC Challenges & Opportunities • Inferior CMOS components compared to discrete counterparts using bipolar, GaAs technologies • Power, size, bandwidth limitations for on-chip • Need an extremely tight control of chip, package parasitic effects on on-chip signals • And yet the system-level capabilities and performance due to • architectural design that is less sensitive to device/technology limitations • system optimizations that include the entire software, networking (and even communications) stack • The requires ability to carry out the architectural design and exploration for SOCs

  5. Systems Engineering for SOCs Example Problem: How to achieve high throughput in a SOC for wireless applications? • Can select a modem sub-system • that packs more bits/Hz, but it will tolerate less noise and be less robust so that link throughput may not improve • Can increase transmit power in RF subsystem • to improve robustness but this increases energy cost, reduces network capacity, and requires more expensive analog circuits (power amps) • Can reduce bits/frame • to tolerate higher bit error rates (BER) and provide more robustness, but this may increase overhead and queuing delays • Can increase precision in digital modem • to reduce noise, but this leads to wider on-chip busses and more power consumption • The design technology must support right sub-system option and parametric determination.

  6. Platform Based Design • A platform is a realized design pattern • provides a well-defined abstraction of the underlying architecture for the application developer • a restriction on the implementation space, captures good solutions • uses components and their reuse within architectural constraints • IP design needs a framework consisting of • component libraries, composition glue, validation, synthesis • complete system simulations, composability and reuse • Key elements for composability • identification of useful models of computation • FSMD, DE, DF, CSP, .. • a flexible, extensible language platform for capture • Component Composition Framework (CCF)

  7. System designer Interpreted Component Integration, CIL Split-Level Interface/BIDL Compiled C++, SystemC BALBOA Component Composition • A layered development and runtime environment • Functionality: describe & synthesize • Structure: capture & simulate • Use an interpreted language for • Architecture description • Component integration • Use compiled models for • behavioral description, simulation • Automatically link the two domains • through a “split-level” interface • Automatic code “wrapper” generation • for component reuse. Software architecture that enables • composition of structural and functional info. • type inference for polymorphic ports • modeling of the application and the platform

  8. Definitions • Component: • A unit of re-use with an interface and an implementation • Meta-information: • Information about the structure and characteristics of an object • Reification: • A data structure to capture the meta-information about the structure and the properties of the program • Reflection: • An architectural technique to allow a component to provide the meta- information to himself • Introspection: • The capability to query and modify the reified structures by a component itself or by the environment 5 ports adder

  9. Introspection SLI/Type system extension Reflection BALBOA Language & Run-time Language Tools Run-time structure CIL Interpreter BIDL BIDL Compiler Split Level Interfaces GCC C++ Compiled objects GCC

  10. Introspective Interfaces for Analysis

  11. Design Example: Adaptive Cache Controller

  12. #load the AMRM component library load ./libamrm.so Entity mem_sys Cache mem_sys.L1 Memory mem_sys.Mem Queue mem_se.r_q L1.upper_request link_to ms.r_q Mem.request_in link_to ms.r_q Tb add_stimuli 100 read 0x399 Tb add_tcl_callback ms.r_q.activity { simulator.do_something; } simulator run 200 CIL Script Example

  13. Number of C++ classes Number of CIL lines Number of BIDL line IP vs Generated C++ code size ratio 7 C++ < 30 60 812/809 (1.01) 8 C++ with SystemC < 40 84 1512/1002 (1.51) 7 C++ with SystemC < 150 87 1437/880 (1.63) Design Example: Cache Controller Manipulate only the script! Script size vs C++ ratio: 1 is to 10

  14. Composition Framework • Dynamically adapt, control and debug complete system models • Using “script-like” interfaces and mixed compiled and interpreted programming components • Component introspection through the reflection enables IP reuse • Create “Virtual” System Architectures • Include application and system software in the model • Exploit full potential of SOC architectural platforms • by exploring runtime system services suitable for SOC applications • example: dynamic power management

  15. Co-simulation libraries HW wrapper libraries Simulator libraries Processor libraries Channel libraries Protocol libraries Virtual System Architectures Extended SystemC Virtual Architecture OS libraries APIs Custom OS Generation HW Wrapper Generation Communication and System Services RTL Architecture Device Drivers RTL Synthesis and Compilation Co-simulation Wrapper Generation Executable Co-simulation Model Emulation platform Cesario, et al, IEEE D&T 11/02

  16. OS-directed Power Management for SOCs • Significant opportunities in power management lie with application-specific “knobs” • quality of service, timing criticality of various functions • Collaboration between applications and the OS in setting “energy use policy” • OS helps resolve conflicts and promote cooperation • The enable OS-directed dynamic power management, we need: • OS should incorporate application information in DPM policy • OS should expose power state and events to applications for these to adapt.

  17. Power Aware Software Architecture • PA-API (Power Aware API) • interfaces applications and OS making the power aware OS services available to the application writer. • PA-OSL (Power Aware Operating System Layer) • implements modified OS services and active components such as a DPM manager. • PA-HAL (Power Aware Hardware Abstraction Layer) • interfaces OS and Hardware making the power control knobs available to the OS programmer.

  18. Current Status • API available from http://www.ics.uci.edu/~cpereira/pads • Implementation on eCOS RTOS and • Hardware platforms we are currently working with: • Linux-synthetic (emulation of eCos over Linux - debugging purposes only) • Compaq iPaq Pocket PC - StrongARM SA1110 based platform • Accelent IDP (Integrated Development Environment) - also StrongARM SA1110 based. • LRH Intel evaluation board 80200EVB - Intel Xscale2 based

  19. Task Application WCET (us) Std Dev (us) T1 MPEG2 (wg_gdo_1.mpg) 30700 3100 T2 MPEG2 (wg_cs_1.mpg) 26300 2100 T3 ADPCM 9300 3300 T4 FFT 15900 0 T5 FFT (gaussian distribution) 13600 800 OS-directed DVS Results

  20. Using Application-level “knob” • Example: Image Compression Algorithm • tradeoff image quality against energy available by varying the compression parameters such as BPP (bits per pixel) • The image compression algorithm is ran in a continuous loop with battery polling every 10 secs. • A simple power tradeoff policy is added to adapt the quality of the image against the battery voltage left. • Whenever the battery drops 30mV the application adjusts the image BPP by -0.5 starting at 1.5. • For a cut-off of 4020mV, the battery life is extended from 290 seconds to 340 seconds.

  21. Instrumented wide-area spaces Internet end-points In-body, in-cell, in-vitro spaces Personal area spaces Summary: Computers with Radios are Leading to New “Spaces” • Generational shift in computing devices • lot more of everything: computing, networking, communications • lot less of power, energy, volume, weight, patience • Application is everything, the possibilities are limitless • System architectures are due for an overhaul • the architectures are (radically) changed/challenged • the programming context is changed • the system software contract is changed • new awareness: location, power, timing, reactivity, stability power

  22. The IP Basket The Planned Community “Organically grown” The sacrificial altar Engineered Specialized Ambitious (and never finished) SOC Architectural Design Paradigms

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