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Heterogeneous Computing
in ARM Architecture
Alan Tsai
Business Development Manager
Sept 2012
2
Agenda
Trends in Heterogeneous Computing
GPU Computing with ARM
®
Mali™-T600
series as example
Heterogeneous System Architecture™ (HSA) is
the future
3
Trends in the Industry
Heterogeneous multiprocessing
Established approach for SoC design
Mix of many specialized accelerators, implementing different ISAs
Diverse programming approaches lead to lack of portability
Parallel computation for performance and efficiency
Endorsed at all levels of computer architecture
Parallel programming traditionally difficult
General purpose programmability of GPUs
Massive parallel computation potential
Increasing programmability
4
What is Parallel Computing?
Simply, doing multiple tasks simultaneously
Task-Parallel computing does different tasks concurrently
Reading email, playing music, and surfing the web are all separate tasks
In a multicore system, these can execute simultaneously
Data-Parallel computing does the same operation on a
collection of data concurrently
Adjusting the contrast of the pixels of an image
Each thread executes the same code but with different data
Classic SIMD (single-instruction, multiple-data)
GPU computing is perfect for data-parallel applications
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