Architectural Musings
Rethinking Computer Systems Architecture
Christopher Vick
cvick@qualcomm.com
June 3, 2012
1
Introduction
 Vision Talk
2
 Mobile computing and current technologies fundamentally
change key parameters and constraints for computer
system architecture
 Vast new opportunities for research of great interest to
and great relevance for industry
Outline
 Computer System Architecture
 Then (Circa 1970)
 Scarce Resources & Bottlenecks
 Optimizations
 Now (Mobile Computing Platforms)
 Scarce Resources & Bottlenecks
 Optimizations?
 Qualcomm Research
 Questions?
3
COMPUTER SYSTEM
ARCHITECTURE
4
Computer System Architecture
 Hardware
 The 5 classic components (Patterson & Hennessy)
 Input, Output, Memory, Datapath, Control
 Software
 System Virtual Machine (Hypervisor, VM, or VMM)
 Operating System
 Compilers & Tools
 Definitions
 The way components fit together
 The arrangement of the various devices in a complete computer system or
network
 The instruction set plus a model of the execution of the instruction set
(Amdahl et al)
 Computer System Architecture
 The selection and combination of hardware and software components to
assemble an effective computer system
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Combination
Application Programs
Libraries
Operating System
Drivers
Memory
Manager
Scheduler
Hypercall Interface
Virtual Machine
Multicore Execution Unit
Interconnect
IO Devices
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Memory
S
o
f
t
w
a
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e
H
a
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d
w
a
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e
Effective
 An optimization problem
 Many variables
 Selection of hardware/software components
 Selection of interfaces/interconnects
 Many constraints
 Physical, sociological, technical & cost constraints
 Scarce Resources and Bottlenecks
 Maximize utilization of scarce resources
 Minimize impact of bottlenecks
7
THEN
(CIRCA 1970)
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Scarce Resources
 CPU Cycles
 CPUs expensive
 Slow clock rates
 Memory Locations
 Random Access Memory expensive
 Address/Data paths into CPU expensive
 Skilled Programmers
 Relatively new discipline
 Poor language and tools support
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Bottlenecks
 Programmer Productivity
 Software development slow and expensive
 Low level programming paradigms
 Memory Latency
 RAM latency gated overall speed (~2-3 MHz)
 Small RAM backed by vastly slower storage
 I/O Bandwidth
 Limited CPU connectivity
 Crude communication mechanisms
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Optimizations
 Time Sharing
 Effective sharing of limited resource
 Virtual Memory
 Effective sharing, and backing with cheaper alternative
 Hardware Improvements
 Smaller features provide more resource and faster clock
 Large Scale Integration
 Better signaling to improve bandwidth
 High Level Programming Languages
 Broadens productive programmer community
 Abstracts away some hardware complexity
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Examples
 Digital PDP 11




16-bit address space
Orthogonal instruction set
Memory mapped I/O
Unix, DOS, many others
 IBM System 370




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24-bit address space
Virtual Memory
VMS, VM/370, DOS/VS
Backward compatibility with System 360
NOW
(MOBILE COMPUTING)
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Scarce Resources
 Energy




Fixed Energy Budget for mobile devices
Thermal issues at all scales
Tradeoff between performance and energy
Shrinks no longer significantly improving consumption
 Memory Bandwidth
 Providing bandwidth is expensive
 Memory interconnect consumes significant energy
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Bottlenecks
 Memory Latency
 Increasing gap between CPU speed and DRAM latency
 Physical distance to DRAM devices a factor
 Concurrency
 Shortage of programmers who can handle this
 Inadequate language/tools support
 I/O Bandwidth/Latency
 Wireless bandwidth lower than wired
 Consumes large amounts of energy
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Example
 HTC One






Processor: 1.5 GHz Dual Core Qualcomm MSM8960
OS: Android™ 4.0 (ICS)
Memory RAM: 1 GB DDR2
Memory Storage: 16 GB onboard storage
Display: 4.7" HD super LCD 1280 x 720
Network: LTE CAT3 - DL 100 /UL 50 LTE: 700/AWS
WCDMA: 2100/1900/AWS/850
EDGE: 850/900/1800/1900
 Battery: 1800 mAh
 Camera (Main): 8 MP, f/2.0, BSI, 1080p HD Video
(Front): 1.3 MP with 720p video
 Dimensions: 134.8 x 69.9 x 8.9mm
 This is a General Purpose Computer!
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Optimizations?
 Multi-core
 Aggressive addition of cores and threads
 Hardware concurrency outstripping software
 New Concurrent Programming Models/Tools?
 Memory Subsystem
 Significant contributor to total energy consumption
 Adding bandwidth is expensive
 New technologies addressing some energy issues
 Wireless bandwidth enhancements (LTE Advanced,etc.)
 Solutions from desktop/server or embedded worlds
may not directly apply in mobile space!
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Memory System Energy
 Retaining data (one second)
 DRAM: ~1-10 pJ/bit self-refresh
 SRAM: 1200+ pJ/bit, and rising over time [ITRS 2009]
 4 pJ/bit (45nm LP, standby) [Barasinski et al., ESSCIRC ‘08]
 Flash, PCM, STT RAM…: Zero !
 Moving Data
 32-bit value:




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Recompute: 60 pJ (Razor)
Send 1mm: 10 pJ
Retain in cache for 1 ms: 38 pJ
Retain in DRAM for 1 second: 32+ pJ
Reducing Memory System Energy
 Move less!
 Caches physically close to CPU
 Locality, locality, locality (the first rule of chip real estate)
 Retain less!
 Power off unused caches lines [Kaxiras et al., ISCA ‘01]
 “Drowsy” caches [Flautner et al., ISCA ‘02]
 … with compiler analysis
[Zhang et al., Trans. Emb. Comp. Sys. 4(3) 2005]
 Don’t refresh unused DRAM
 … e.g. with garbage collection [Chen et al., CODES+ISSS ‘03]
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Extending the Memory Model
 Maintaining the illusion of a single flat memory address
space is too expensive
 On-chip caches can be major consumers of area and energy
 Coherence protocols are expensive and difficult to scale
• Alternative: software-managed memory hierarchies
– Tightly-coupled memory (TCM), scratchpads
– Do not require tag memory, address comparison logic
– More area- and energy-efficient
– Help bridge gap between bandwidth and throughput
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New Challenges and Opportunities
 Different programming paradigm: software explicitly
orchestrates all transfers between on-chip and off-chip
memory areas
 Major implications on memory management
 Scratchpad allocation strategies
 Data partitioning strategies
 Dynamic relocation between scratchpad and DRAM to track the
program’s locality characteristics
 Opportunities for compile-time and runtime optimization
 Challenges in both Hardware and Software!
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Qualcomm Research
Excellence in Wireless
MAY | 2012
WWW.QUALCOMM.COM/RESEARCH
State of the Art Capabilities Fostering Innovation
2323
Human Resources
Complete Development Labs
• 30% of engineers with PhD,
50% Masters
• Prototype Development Facilities
• Systems, HW, SW, Standards,
Test Engineering
• CPU Simulation Clusters
• Ventures, Bus Dev, Technical
Marketing, Program Mgmt.
• Outdoor Field Systems
• Antenna Ranges
Global Research and Development
Organization
UNITED STATES
EUROPE
ASIA
• San Diego, CA
• Cambridge, UK
• Beijing, China
• Santa Clara, CA
• Nuremberg, Germany
• Bridgewater, NJ
• Vienna, Austria
• Bangalore and
Hyderabad, India
• Seoul, S. Korea
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Qualcomm Research & University Relations
ACADEMIC COLLABORATION TO FOSTER ADVANCED RESEARCH
RESEARCH
Ongoing relations with more than 30 US and 25 International Universities
 Current funding includes MIT, UC Berkeley, Stanford, UCSD, UT Austin, ASU,
UIUC, Univ. of Michigan, EPFL, IISc Bangalore, KAIST, Tsinghua
Research collaboration spans variety of technical areas
 Computer vision, multicore processing, context aware computing, machine
learning, low power devices,, wireless networks and signal processing, etc..
Qualcomm Innovation Fellowship (QInF) invests on innovative ideas
 Close interactions between Qualcomm Research engineers, graduate students and
professors
25
Qualcomm Research For The Wireless
Future
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TAKE WWAN TO
THE NEXT LEVEL
INNOVATE
BEYOND WAN
ENABLE SMART
APPLICATIONS
BREAKTHROUGH
PERFORMANCE
IMPROVING WWAN
TECHNOLOGY
EXCELLING IN ALL
FORMS OF
WIRELESS
TRANSFORMING
THE MOBILE USER
EXPERIENCE
RE-ARCHITECTING
NEXT-GEN MOBILE
DEVICES
Innovate Beyond WAN
WIRELESS LOCAL AREA
PEANUT
WIFI ADVANCED
• Next gen short range
ultra-low power radio
• Multi Gbps WLAN using 5
GHz and 60 GHz band.
• Next Gen low-power WiFi
for Internet of Things
LTE D2D
(FLASHLINQ)
• Proximal Wireless
• First Gen device-todevice wireless network
• Autonomous discovery
• Direct communications
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INNAV
• Indoor positioning for indoor
location based applications
• Map tools for Mobile
Devices
Enable Smart Applications
ELEVATE THE WIRELESS USER EXPERIENCE
AUGMENTED
REALITY
• Mobile user
interface
• Computer vision for
mobile devices
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LOOK
• Multiple language
text detection and
recognition
• With Mobile phone
camera view finder
LISTEN
• Background Audio
processing
• Augmented user
experience
DASH
• Efficient video
delivery over
HTTP for mobile
devices
AWARE
• Build awareness
in mobile devices
• For enhanced
daily life situations
Breakthrough Device Performance
RE-ARCHITECTING NEX-GEN DEVICES
ADVANCED RADIO
TECHNOLOGIES
• New RF front-end and
baseband technologies
• Advanced mobile device
SW platforms
• RF/antenna and
systems/protocol
techniques
• Improved user
experience
• Concurrent multi-radio
operation
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MANTICORE
GRYPHON
• Virtual machine
design for SoC
architecture
• Enabling higher power
efficiency
Thank You