Computation Spreading: Employing
Hardware Migration to Specialize CMP
Cores On-the-fly
Koushik Chakraborty Philip Wells
Gurindar Sohi
{kchak,pwells,sohi}@cs.wisc.edu
1
Paper Overview
 Multiprocessor Code Reuse
Poor resource utilization
 Computation Spreading
New model for assigning computation within
a program on CMP cores in H/W
Case Study: OS and User computation
 Investigate performance characteristics
Chakraborty, Wells, and Sohi
ASPLOS 2006
2
Talk Outline
 Motivation
 Computation Spreading (CSP)
Case study: OS and User compution
 Implementation
 Results
 Related Work and Summary
Chakraborty, Wells, and Sohi
ASPLOS 2006
3
Homogeneous CMP
 Many existing systems are homogeneous
Sun Niagara, IBM Power 5, Intel Xeon MP
 Multithreaded server application
Composed of server threads
Typically each thread handles a client request
OS assigns software threads to cores
• Entire computation from one thread execute on
a single core (barring migration)
Chakraborty, Wells, and Sohi
ASPLOS 2006
4
Code Reuse
 Many client requests are similar
Similar service across multiple threads
Same code path traversed in multiple cores
 Instruction footprint classification
Exclusive – single core access
Common – many cores access
Universal – all cores access
Chakraborty, Wells, and Sohi
ASPLOS 2006
5
Multiprocessor Code Reuse
Chakraborty, Wells, and Sohi
ASPLOS 2006
6
Implications
 Lack of instruction stream specialization
Redundancy in predictive structures
• Poor capacity utilization
Destructive interference
 No synergy among multiple cores
Lost opportunity for co-operation
Exploit core proximity in CMP
Chakraborty, Wells, and Sohi
ASPLOS 2006
7
Talk Outline
 Motivation
 Computation Spreading (CSP)
Case study: OS and User compution
 Implementation
 Results
 Related Work and Summary
Chakraborty, Wells, and Sohi
ASPLOS 2006
8
Computation Spreading (CSP)
 Computation fragment = dynamic instruction
stream portion
 Collocate similar computation fragments from
multiple threads
Enhance constructive interference
 Distribute dissimilar computation fragments
from a single thread
 Reduce destructive interference
Reassignment is the key
Chakraborty, Wells, and Sohi
ASPLOS 2006
9
Example
time
T1 T2 T3
A1 B2 C3
B1 C2 A3
C1 A2 B3
C
A
N
O
N
I
C
A
L
A1 B2 C3
B1 C2 A3
C1 A2 B3
P1 P2 P3
A1 B2 C3
C
S
P
A3 B1 C2
A2 B3 C1
Chakraborty, Wells, and Sohi
ASPLOS 2006
10
Key Aspects
Dynamic Specialization
Homogeneous multicore acquires specialization via
retaining mutually exclusive predictive state
Data Locality
Data dependencies between different computation
fragments
Careful fragment selection to avoid loss of data
locality
Chakraborty, Wells, and Sohi
ASPLOS 2006
11
Selecting Fragments
Server workloads characteristics
Large data and instruction footprint
Significant OS computation
User Computation and OS Computation
A natural separation
Exclusive instruction footprints
Relatively independent data footprint
Chakraborty, Wells, and Sohi
ASPLOS 2006
12
Data Communication
Core 1
Core 2
T1-User
T2-User
T1
T2
T1-OS
T2-OS
Chakraborty, Wells, and Sohi
ASPLOS 2006
13
Relative Inter-core Data
Communication
Apache
OLTP
OS-User Communication is limited
Chakraborty, Wells, and Sohi
ASPLOS 2006
14
Talk Outline
 Motivation
 Computation Spreading (CSP)
Case study: OS and User compution
 Implementation
 Results
 Related Work and Summary
Chakraborty, Wells, and Sohi
ASPLOS 2006
15
Implementation
Migrating Computation
Transfer state through the memory subsystem
• ~2KB of register state in SPARC V9
• Memory state through coherence
Lightweight Virtual Machine Monitor
Migrates computation as dictated by the CSP Policy
Implemented in hardware/firmware
Chakraborty, Wells, and Sohi
ASPLOS 2006
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Threads
Implementation cont
Software
Stack
Virtual CPUs
OS Comp
User Comp
Physical
Cores
User Cores
Chakraborty, Wells, and Sohi
Baseline
OS Cores
ASPLOS 2006
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Threads
Implementation cont
Software
Stack
Virtual CPUs
Physical
Cores
User Cores
Chakraborty, Wells, and Sohi
OS Cores
ASPLOS 2006
18
CSP Policy
Policy dictates computation assignment
Thread Assignment Policy (TAP)
Maintains affinity between VCPUs and
physical cores
Syscall Assignment Policy (SAP)
OS computation assigned based on system
calls
TAP and SAP use identical assignment for
user computation
Chakraborty, Wells, and Sohi
ASPLOS 2006
19
Talk Outline
 Motivation
 Computation Spreading (CSP)
Case study: OS and User compution
 Implementation
 Results
 Related Work and Summary
Chakraborty, Wells, and Sohi
ASPLOS 2006
20
Simulation Methodology
 Virtutech SIMICS MAI running Solaris 9
 CMP system: 8 out-of-order processors
2 wide, 8 stages, 128 entry ROB, 3GHz
 3 level memory hierarchy
Private L1 and L2
Directory base MOSI
L3: Shared, Exclusive 8MB (16w) (75 cycle load-to-use)
Point to point ordered interconnect (25 cycle latency)
Main Memory 255 cycle load to use, 40GB/s
Measure impact on predictive structures
Chakraborty, Wells, and Sohi
ASPLOS 2006
21
L2 Instruction Reference
Chakraborty, Wells, and Sohi
ASPLOS 2006
22
Result Summary
 Branch predictors
9-25% reduction in mis-predictions
 L2 data references
0-19% reduction in load misses
Moderate increase in store misses
 Interconnect messages
Moderate reduction (after accounting extra
messages for migration)
Chakraborty, Wells, and Sohi
ASPLOS 2006
23
Performance Potential
Migration Overhead
Chakraborty, Wells, and Sohi
ASPLOS 2006
24
Talk Outline
 Motivation
 Computation Spreading (CSP)
Case study: OS and User compution
 Implementation
 Results
 Related Work and Summary
Chakraborty, Wells, and Sohi
ASPLOS 2006
25
Related Work
 Software re-design: staged execution
Cohort Scheduling [Larus and Parkes 01], STEPS
[Ailamaki 04], SEDA [Welsh 01], LARD [Pai 98]
CSP: similar execution in hardware
 OS and User Interference [several]
Structural separation to avoid interference
CSP avoids interference and exploits synergy
Chakraborty, Wells, and Sohi
ASPLOS 2006
26
Summary
 Extensive code reuse in CMPs
45-66% instruction blocks universally accessed in
server workloads
 Computation Spreading
Localize similar computation and separate
dissimilar computation
Exploits core proximity in CMPs
 Case Study: OS and User computation
Demonstrate substantial performance potential
Chakraborty, Wells, and Sohi
ASPLOS 2006
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Thank You!
Chakraborty, Wells, and Sohi
ASPLOS 2006
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Backup Slides
Chakraborty, Wells, and Sohi
ASPLOS 2006
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L2 Data Reference
L2 load miss comparable, slight to moderate increase
in L2 store miss
Chakraborty, Wells, and Sohi
ASPLOS 2006
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Multiprocessor Code Reuse
Chakraborty, Wells, and Sohi
ASPLOS 2006
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Performance Potential
Chakraborty, Wells, and Sohi
ASPLOS 2006
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