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Department of Electrical Engineering
Electronic Systems
Mapping applications to predictable MPSoCs
Sander Stuijk, Marc Geilen, Twan Basten
HiPEAC 2013 tutorial
Berlin, Germany
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2 Embedded streaming systems
Application trends
Uncertainty
Concurrency
Dynamism
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3 Model-based design
Design flow
+
....
Modeling
Analysis
Implementation
Run-time management
App 1 App 2
+ =
Gantt chart
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4 WLAN application
New OFDM symbol every 4.0 μs
Sync, Header, Payload scenario process one symbol
CRC processes no symbol
Ports may have rates
Rate one omitted for clarity
Initial tokens return to original distribution after one iteration
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5 WLAN application
Each scenario may be modeled with a different scenario graph
Persistent token names provide relation between initial tokens in different
scenario graphs
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6
shift
src
sync
Src
0 μS 4 μS 8 μS 12 μS
Shift
Sync
Hdem
Hdec
Pars
pars
WLAN application
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7
shift
src
sync
Src
0 μS 4 μS 8 μS 12 μS
Shift
Sync
Hdem
Hdec
Pars
pars
sync
WLAN application
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8 WLAN application
shift
src
sync
Src
header
0 μS 4 μS 8 μS 12 μS
Shift
Sync
Hdem
Hdec
Pars
pars
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9
src
shift
pars
src
shift
pars
Sync Header
4000 ns
5940 ns
0 ns
Analyzing SADF graphs
Gantt chart for one scenario sequence
Execution is a sequence of vector shapes
Token time stamps (vector shapes) provide constraints for next iteration
shift
src
sync
Src
header
0 μS 4 μS 8 μS 12 μS
Shift
Sync
Hdem
Hdec
Pars
pars
delay
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10
src
shift
pay-
load
pars
src
shift
pay-
load
pars
src
shift
pay-
load
pars
src
shift
pay-
load
pars
Sync Header Payload CRC
5940 ns
0 ns
4000 ns, 1
0 ns, 0
4000 ns, 1
4000 ns, 1
4000 ns, 1
4000 ns, 1
4000 ns, 1
4000 ns, 1
Analyzing SADF graphs
Max-plus automaton
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11 Analyzing SADF graphs
Throughput: MCM/MCR
Latency: longest-path
src
shift
pay-
load
pars
src
shift
pay-
load
pars
src
shift
pay-
load
pars
src
shift
pay-
load
pars
Sync Header Payload CRC
5940 ns
0 ns
4000 ns, 1
0 ns, 0
4000 ns, 1
4000 ns, 1
4000 ns, 1
4000 ns, 1
4000 ns, 1
4000 ns, 1
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12 Analyzing buffer/throughput trade-off
Model buffer size constraints with back-edge with initial tokens
buffer size of 1 token/edge
enlarge buffer size to 2 tokens
throughput
analysis
throughput
analysis
<4.0 μs/symbol
4 μs/symbol
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13
pars
Predictable scenario-aware design-flow
Design flow
+
....
?
Tile 1
EVP
interconnect
NI
IMEM
DMEM
Tile 2
SWC
NI
IMEM
DMEM
Tile 2
ARM
NI
IMEM
DMEM
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14
Predictable scenario-aware design-flow
Compute buffer constraints
+
....
thro
ug
hp
ut
distribution size
scenario sync
thro
ug
hp
ut
distribution size
scenario header
thro
ug
hp
ut
distribution size
combined
pars
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15
pars
Tile 1
EVP
interconnect
NI
IMEM
DMEM
Tile 2
SWC
NI
IMEM
DMEM
Tile 2
ARM
NI
IMEM
DMEM
Predictable scenario-aware design-flow
pars
resource
sharing
Compute buffer constraints
Unified resource binding
Static-order scheduling
+
....
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16
Tile 1
EVP
interconnect
NI
IMEM
DMEM
Tile 2
SWC
NI
IMEM
DMEM
Tile 2
ARM
NI
IMEM
DMEM
Predictable scenario-aware design-flow
communication delay
pars
resource
sharing
Compute buffer constraints
Unified resource binding
Static-order scheduling
+
....
pars
D
D
parspars
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17
src
shift
payload
pars
evp
swc
arm
ofdm symbolevp active
swc activearm active
0 μs 4 μs 8 μs 12 μs 16 μs 20 μs
sync header payload
crc
WLAN application
Initial tokens of resources capture resource availability
Timing requirements seems to be met...
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18 Model-based design
Design flow
+
....
Modeling
Analysis
Implementation
Run-time management
App 1 App 2
+ =
Gantt chart
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19 Run-time reconfiguration
DVFS changes actor
execution times
DVFS settings modeled with
system scenarios
pars
Tile 1
EVP
interconnect
NI
IMEM
DMEM
Tile 2
SWC
NI
IMEM
DMEM
Tile 2
ARM
NI
IMEM
DMEM
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20 WLAN application
Latency between reception of OFDM symbol and processing increases
Processing cannot keep up with frequent reconfiguration
src
shift
payload
pars
evp
swc
arm
ofdm symbolevp active
swc activearm active
0 μs 4 μs 8 μs 12 μs 16 μs 20 μs 24 μs 28 μs 32 μs 36 μs
sync-c1 header-c1 payload-c1 sync-c2 header-c2 payload-c2 sync-c1 header-c1 payload-c1
crc-c1Reconf
c1 → c2 crc-c2Reconf
c2 → c1
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21 Summary
Strategy for designing predictable systems running dynamic applications
Scenarios capture dynamic (application and system) behavior
Resource and energy efficient implementations
Predictable implementations
SADF Model-of-Computation
Provides many analysis techniques
Provides implementation trajectory
Analysis and implementation techniques implemented in SDF3 tool kit
www.es.ele.tue.nl/sdf3