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Boosting Mobile GPU Performance with a Decoupled Access/Execute
Boosting Mobile GPU Performance with a Decoupled Access/Execute
Focusing on Mobile GPUs
Focusing on Mobile GPUs
Focusing on Mobile GPUs
Focusing on Mobile GPUs
Focusing on Mobile GPUs
Focusing on Mobile GPUs
Assumed GPU Architecture
Assumed GPU Architecture
Assumed Fragment Processor
Assumed Fragment Processor
Methodology
Methodology
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Workload Selection
Improving Performance Using Multithreading
Improving Performance Using Multithreading
Employing Prefetching
Employing Prefetching
Employing Prefetching
Employing Prefetching
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Inter-Core Data Sharing
Inter-Core Data Sharing
Inter-Core Data Sharing
Inter-Core Data Sharing
Inter-Core Data Sharing
Inter-Core Data Sharing
Inter-Core Data Sharing
Inter-Core Data Sharing
Inter-Core Data Sharing
Inter-Core Data Sharing
Inter-Core Data Sharing
Inter-Core Data Sharing
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Decoupled Access/Execute
Benefits of Remote L1 Cache Accesses
Benefits of Remote L1 Cache Accesses
Benefits of Remote L1 Cache Accesses
Benefits of Remote L1 Cache Accesses
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Автор: Jose Arnau. Чтобы познакомиться с картинкой полного размера, нажмите на её эскиз. Чтобы можно было использовать все картинки для урока английского языка, скачайте бесплатно презентацию «Boosting Mobile GPU Performance with a Decoupled AccessExecute Fragment Processor.ppt» со всеми картинками в zip-архиве размером 2609 КБ.

Boosting Mobile GPU Performance with a Decoupled AccessExecute Fragment Processor

содержание презентации «Boosting Mobile GPU Performance with a Decoupled AccessExecute Fragment Processor.ppt»
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1Boosting Mobile GPU Performance with a 936 KB MRF for a GPU with 16 warps/core
Decoupled Access/Execute Fragment (bigger than L2). Jose-Maria Arnau,
Processor. Jos?-Mar?a Arnau, Joan-Manuel Joan-Manuel Parcerisa, Polychronis
Parcerisa (UPC) Polychronis Xekalakis Xekalakis. 9.
(Intel). 10Employing Prefetching. Hardware
2Focusing on Mobile GPUs. prefetchers: Global History Buffer K. J.
Energy-efficient mobile GPUs. Market Nesbit and J. E. Smith. “Data Cache
demands. Technology limitations. 1. 2. Prefetching Using a Global History
Jose-Maria Arnau, Joan-Manuel Parcerisa, Buffer”. HPCA, 2004. Many-Thread Aware J.
Polychronis Xekalakis. 2. 1 Lee, N. B. Lakshminarayana, H. Kim and R,
http://www.digitalversus.com/mobile-phone/ Vuduc. “Many-Thread Aware Prefetching
amsung-galaxy-note-p11735/test.html Mechanisms for GPGPU Applications”. MICRO,
Samsung galaxy SII vs Samsung Galaxy Note 2010. Prefetching is effective but there
when running the game Shadow Gun 3D 2 is still ample room for improvement.
http://www.ispsd.com/02/battery-psd-templa Jose-Maria Arnau, Joan-Manuel Parcerisa,
es/. Polychronis Xekalakis. 10.
3GPU Performance and Memory. A mobile 11Decoupled Access/Execute. Use the
single-threaded GPU with perfect caches fragment information to compute the
achieves a speedup of 3.2x on a set of addresses that will be requested when
commercial Android games. Graphical processing the fragment Issue memory
workloads: Large working sets not amenable requests while the fragments are waiting
to caching Texture memory accesses are in the tile queue Tile queue size: Too
fine-grained and unpredictable Traditional small: timeliness is not achieved Too big:
techniques to deal with memory: Caches cache conflicts. Jose-Maria Arnau,
Prefetching Multithreading. Jose-Maria Joan-Manuel Parcerisa, Polychronis
Arnau, Joan-Manuel Parcerisa, Polychronis Xekalakis. 11.
Xekalakis. 3. 12Inter-Core Data Sharing. 66.3% of
4Outline. Background Methodology cache misses are requests to data
Multithreading & Prefetching Decoupled available in the L1 cache of another
Access/Execute Conclusions. Jose-Maria fragment processor Use the prefetch queue
Arnau, Joan-Manuel Parcerisa, Polychronis to detect inter-core data sharing Saves
Xekalakis. 4. bandwidth to the L2 cache Saves power (L1
5Assumed GPU Architecture. Jose-Maria caches smaller than L2) Associative
Arnau, Joan-Manuel Parcerisa, Polychronis comparisons require additional energy.
Xekalakis. 5. Jose-Maria Arnau, Joan-Manuel Parcerisa,
6Assumed Fragment Processor. Warp: Polychronis Xekalakis. 12.
group of threads executed in lockstep mode 13Decoupled Access/Execute. 33% faster
(SIMD group). 4 threads per warp 4-wide than hardware prefetchers, 9% energy
vectorial registers (16 bytes) 36 savings DAE with 2 warps/core achieves 93%
registers per thread. Jose-Maria Arnau, of the performance of a bigger GPU with 16
Joan-Manuel Parcerisa, Polychronis warps/core, providing 34% energy savings.
Xekalakis. 6. Jose-Maria Arnau, Joan-Manuel Parcerisa,
7Methodology. Main memory. Latency = Polychronis Xekalakis. 13.
100 cycles Bandwidth = 4 bytes/cycle. 14Benefits of Remote L1 Cache Accesses.
Pixel/Textures caches. 2 KB, 2-way, 2 Single threaded GPU Baseline: Global
cycles. L2 cache. 32 KB, 8-way, 12 cycles. History Buffer 30% speedup 5.4% energy
Number of cores. 4 vertex, 4 pixel savings. Jose-Maria Arnau, Joan-Manuel
processors. Warp width. 4 threads. Parcerisa, Polychronis Xekalakis. 14.
Register file size. 2304 bytes per warp. 15Conclusions. High performance, energy
Number of warps. 1-16 warps/core. Power efficient GPUs can be architected based on
Model: CACTI 6.5 and Qsilver. Jose-Maria the decoupled access/execute concept A
Arnau, Joan-Manuel Parcerisa, Polychronis combination of decoupled access/execute
Xekalakis. 7. -to hide memory latency- and
8Workload Selection. 2D games. Simple multithreading -to hide functional units
3D games. Complex 3D games. Small/medium latency- provides the most energy
sized textures Texture filtering: 1 memory efficient solution Allowing for remote L1
access Small fragment programs. cache accesses provides L2 cache bandwidth
Small/medium sized textures Texture savings and energy savings The decoupled
filtering: 1-4 memory accesses access/execute architecture outperforms
Small/medium fragment programs. Medium/big hardware prefetchers: 33% speedup, 9%
sized textures Texture filtering: 4-8 energy savings. Jose-Maria Arnau,
memory accesses Big, memory intensive Joan-Manuel Parcerisa, Polychronis
fragment programs. Jose-Maria Arnau, Xekalakis. 15.
Joan-Manuel Parcerisa, Polychronis 16Boosting Mobile GPU Performance with a
Xekalakis. 8. Decoupled Access/Execute Fragment
9Improving Performance Using Processor. Thank you! Questions?
Multithreading. Very effective High energy Jos?-Mar?a Arnau (UPC) Joan-Manuel
cost (25% more energy) Huge register file Parcerisa (UPC) Polychronis Xekalakis
to maintain the state of all the threads (Intel).
Boosting Mobile GPU Performance with a Decoupled AccessExecute Fragment Processor.ppt
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