This presentation discusses the Mantle API, what it is, why choose it, and abstraction level, small batch performance and platform efficiency. Download the presentation from the AMD Developer website here: http://bit.ly/TrEUeC

1. MANTLE
THE SMALL BATCH (AND OTHER)
SOLUTIONS IN MANTLE API
GUENNADI RIGUER – MANTLE CHIEF ARCHITECT

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Problems
Abstraction level
Small batch performance
Platform efficiency

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Wrong Abstraction Level
Unpredictable big black box
Current situation: neither fast nor simple
Too high to be fast, too low to be simple

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Small Batch Performance
10K
100K
Most games today
Really optimized games
Where you want to be (Mantle target)

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Previous Solutions
Geometry instancing
Geometry shaders
Texture atlases & arrays
Uber-shaders
Command recorders
…

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Why They Failed?
Development and content creation limitations
Trading driver overhead for engine performance
Trading CPU performance for GPU overhead

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What is Mantle?
Lower level API
Focus on performance
Empower developers to do what they want

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Why Mantle?
Better performance
Predictable performance
Developer control

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Key Features

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Execution Model
Graphics
Compute
DMA
GPU
. . .
Queues
Application
App thread
App thread
App thread
App thread
App thread

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Execution Model
Graphics
Compute
DMA
GPU
. . .
Queues
Application
App thread
App thread
App thread
App thread
App thread

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Execution Model
Graphics
Compute
DMA
GPU
. . .
Application
App thread
App thread
App thread
App thread
App thread
Queues

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Execution Model
Queues
Application
App thread
App thread
App thread
App thread
App thread
Graphics
Compute
DMA
GPU
. . .

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Memory & Resources
Application controls memory
Application handles hazards
Generalized resources

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Pre-build & Pre-validate
Pipelines
Resource binding
Multi-use command buffers

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Platform Considerations
APUs & SOCs are here
No longer CPU vs. GPU
Race to low power

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0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
10K batches 50K batches 100K batches
Mantle
DX11
0
20
40
60
80
100
120
0
2
4
6
8
10
12
14
10K batches 50K batches 100K batches
Mantle FPS
DX11 FPS
Mantle power
DX11 Power
Power Efficiency - StarSwarmFPS Power (W) FPS/W
Starswarm using RTS preset @1080p running on APU A10-7800 @ 3.5GHz, 4GB 2133MHz RAM, A88X-Pro M/B

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Power Efficiency - Games
0
20
40
60
80
100
120
0
10
20
30
40
50
60
BF4 @ 1280x720 BF4 @
1920x1080
Thief - Low @
720x480
Thief - Normal @
1280x720
Mantle FPS
DX11 FPS
Mantle power
DX11 Power
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
BF4 @
1280x720
BF4 @
1920x1080
Thief - Low @
720x480
Thief - Normal
@ 1280x720
Mantle
DX11
FPS Power (W) FPS/W
Battlefield 4 BrokenFlightDeck level @720p and @1080p MEDIUM settings and SSAO enabled running on APU
A10-7800 @ 3.5GHz, 4GB 2133MHz RAM, A88X-Pro M/B
Thief built-in benchmark running on same hardware with low settings at 720x480 and normal settings at 720p

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Lessons Learned

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Think Outside the Box
Don’t just make something faster
…avoid doing it completely
Design API and driver together

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New Driver Design
Even a bit of sync kills many-core performance
“Thick” driver = cache pollution
“Make it the application’s problem” 

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Lots of Little Things…
The whole is greater than the sum of its parts

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Future HW Considerations
HW small batch, anyone?
Command processing bottlenecks
More operations/batches in flight

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Challenges
Programming is harder
Ecosystem must change
Applications must "do the right thing“

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Summary
Mantle fixes abstraction level
Mantle improves platform efficiency
Mantle leads industry transformation

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Questions?

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