Parallel Computing On Qualcomm Platforms Using OpenCL - Uplinq

More documents

Recommendations

Info

Anatomy of an OpenCL Platform • A host computer can have one or more OpenCL devices • Each OpenCL device has one or more compute units • Each compute unit has one or more processing elements OpenCL devices 20 Qualcomm Proprietary
OpenCL Memory Model • Memory Types – Private: on-chip, temp register file – Local: on-chip, read-write, shared within a compute unit – Constant: on-chip memory, read-only, shared within compute unit – Global: system memory, shared between all compute units, can be on host or device • Memory model – OpenCL provides barrier mechanism for synchronization o Memory is assumed to be undefined across work items unless explicitly synchronized – Multiple distinct address spaces – Address spaces can be collapsed depending on the device’s memory subsystem • Diagram shows typical memory layout for a GPU architecture t Private Memory Private Memory Private Memory Private Memory ALU #1 ALU #M ALU #1 ALU #M Local Memory Compute Unit 1 Compute Device Local Memory Compute Unit N Global / Constant Memory Data Cache Global Memory Compute Device Memory 21 Qualcomm Proprietary
Page 1 and 2: Parallel Computing on Qualcomm ® P
Page 3 and 4: OpenCL - The Missing Piece • ”O
Page 5 and 6: Low Light Image Enhancement Effort
Page 7 and 8: 7 Qualcomm Proprietary
Page 9 and 10: General Purpose vs. Custom Devices
Page 11 and 12: Qualcomm OpenCL Plans • Qualcomm
Page 13 and 14: Qualcomm’s OpenCL Platform 1-4 ve
Page 15 and 16: View of Next Generation OpenCL * *
Page 17 and 18: CPUs Multiple cores driving perform
Page 19: However OpenCL Provides for Consist
Page 23 and 24: OpenCL data set decomposition into
Page 25 and 26: Questions End 25 Qualcomm Proprieta
Page 27: Trademarks Qualcomm is a registered

Parallel Computing On Qualcomm Platforms Using OpenCL - Uplinq

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?