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Amd accelerated computing -ufrj

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Roberto Brandao

This document discusses x86 processor evolution, GPUs as accelerators, accelerated processing units (APUs), and OpenCL. It describes how x86 processors are gaining more cores and memory channels over time. It explains how GPUs can accelerate tasks like video transcoding using massively parallel processing. APUs integrate CPU and GPU cores on a single die to improve performance and efficiency. Finally, it introduces OpenCL as an open standard for programming heterogeneous systems like CPUs and GPUs.

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Amd accelerated computing -ufrj
Agenda X86 PROCESSOR EVOLUTION THE GPU AS AN ACCELERATOR ACCELERATED PROCESSING UNITS INTRODUCTION TO OpenCL
Evolving x86 Processors
AMD architecture “Istambul” six-core diagram 1 2 3 4 5 6 Balanced Native caches L2 L2 L2 L2 L2 L2 six-core processor L3 Cache Lower memory latency CROSSBAR Hyper Memory Transport Controller HyperTransport PCI-e Fast full-duplex Chipset bus
4P/24-core system example very good scalability One memory controller for every MEMORY MEMORY processor Full-duplex Hyper Transport links (up to 5.2GHz) MEMORY MEMORY Bus Optimization: HT Assist (Cache Probe Filtering) Still the only available 4P system with Direct Connect Architecture
Direct Connect Architecture 1.0 Balanced and Scalable Design to Support up to 6 Cores CHANNELS 2 MEMORY 2 MEMORY CHANNELS 8 DIMMs 8 DIMMs per CPU per CPU CHANNELS 2 MEMORY 2 MEMORY CHANNELS 8 DIMMs 8 DIMMs per CPU per CPU No front side bus HyperTransport™ technology Integrated memory controller NUMA memory architecture
Direct Connect Architecture 2.0 Balanced and Scalable Design to Support up to 16 Cores* per CPU CHANNELS 4 MEMORY 4 MEMORY CHANNELS 12 DIMMs 12 DIMMs per CPU per CPU CHANNELS 4 MEMORY 4 MEMORY CHANNELS 12 DIMMs 12 DIMMs per CPU per CPU • 1-hop between processors • Four memory channels • Up to 50% more DIMMs • Up to 33% increase in CPU to CPU communication speed±
What is next for x86 CPUs • More processor cores to come (12, 16, 16 double cores) • More memory channels (improves memory bandwidth per core) • Improved IPC (8 per cycle is a target)
Top500 list - beyond the petaflop Datacenters in the USA will spend more than $3 billion on energy in 2009
1997: X Garry Kasparov IBM Deep Blue
The World’s Most Powerful GPU =
2011 GPU Architecture AMD Radeon™ HD 6900 Series Dual graphics engines New VLIW4 core architecture Up to 24 SIMD engines Up to 96 Texture Units Upgraded render back-ends  Improved anti-aliasing performance Fast 256-bit GDDR5 memory interface  Up to 5.5 Gbps New GPU compute features
Designing very efficient GPUs Full load: 180W; Idle:27W 16 14.47 14 GFLOPS/W 12 GFLOPS/W GFLOPS/mm2 10 7.50 8 4.50 7.90 GFLOPS/mm2 6 2.01 2.21 4.56 4 1.07 2.24 2 0.42 1.06 0.92 0 Nov-05 Jan-06 Sep-07 Nov-07 Jun-08 Oct-09 ATI Radeon™ ATI Radeon™ ATI Radeon™ HD ATI Radeon™ HD ATI Radeon™ HD ATI Radeon™ HD X1800 XT X1900 XTX 2900 PRO 3870 4870 5870
Old and New in High Performance Computing Old: Power is free, Transistors are expensive New: Power expensive, Transistors free (Can put more transistors on chip than can afford to turn on) Old: Multiplies are slow, Memory access is fast New: Multiplies fast, Memory slow (up 200 clocks to DRAM memory, 4 clocks for FP multiply) Old: Increasing Instruction Level Parallelism via compilers innovation New: Explicit thread and data parallelism must be exploited
GPUs: more than just gaming Processing power – millions of operations per second Single Core 12 Dual Core 24 Quad Core 48 Hexa Core 72 12 Cores 144 2700 Radeon HD 5970 Both use GPUs Wii Sports - Golf Oil exploration platform - 2010 15
DirectX® 11 Multi-Threading  Application, DirectX runtime, and DirectX driver can each run in separate threads  Tasks like loading a texture or compiling a shader can execute in parallel with main rendering thread DirectX® 10 DirectX® 11 16
Today’s GPUs focused on GAMING ENTERTAINMENT PRODUCTIVITY
DirectX® 11 Tessellation DirectX® 10 DirectX® 11 No Tessellation Tessellation Images courtesy of Unigine Corp. 18
5/26/2011
5/26/2011
Research companies already using Oil exploration Wheather forecast Fluid Dynamics Nature simulation 21
AMD Balanced Platform GPU is ideal for data parallel algorithms CPU is excellent for running some like image processing, CAE, etc algorithms  Great use for ATI Stream  Ideal place to process if GPU is technology fully loaded  Great use for additional GPUs  Great use for additional CPU cores Graphics Workloads Serial/Task-Parallel Other Highly Workloads Parallel Workloads Delivers optimal performance for a wide range of platform configurations
ATI Stream Technology is… Heterogeneous: Developers leverage AMD GPUs and x86 CPUs for optimal application performance and user experience High performance: Massively parallel, programmable GPU architecture delivers unprecedented performance and power efficiency Industry Standards: OpenCL™ and DirectCompute 11 enable cross-platform development Sciences Government Engineering Gaming Digital Productivity Content Creation
Improvements already reached consumers 80% 70% 60% 50% ATI Stream 40% 30% 20% 10% 0% Processor utilization Adobe Flash plugin used by Youtube.com  Better image quality and video smoothness  Lower processor usage
GPU-accelerated video transcoding Ipod Video HD Video Up to 6x faster when using an AMD graphics card
Video Transcoding Sample No GPU Acceleration CPU Usage: 100% Using four CPU Cores GPU Usage: 1% CPU Usage: 100% Time to finish: 1h 52m Total Power: 0.23kW/h GPU Usage: 1% Peak power: 145W Energy Price: $0.15 26
Video Transcoding Sample ATI GPU Acceleration CPU Usage: 45% GPU Usage: 35% Using hundreds of Stream Processors CPU Usage: 45% (100%) Time to finish: 26m (1h52m) Total Power: 0.11kW/h (0.23) GPU Usage: 35% (1%) Peak power: 198W (145W) Energy Price: $0.07 ($0.15) 27
FUSION TECHNOLOGY
Today Multi-core CPU TeraFLOPS-class GPU ~800 million transistors Up to 2 billion transistors Multi-tasking Jogos em multiplos monitores Video e audio Full HD
A new Era on performance evolution Heterogeneous Single-Core Multi-Core computing Challenge: Challenge: Pros: Power consumption Power consumption  Performance Complexity Software  Power efficient Cons: Software availability Single-thread Performance Performance ? We are here We are here We are here Time Time x Cores Time
A new Era on performance evolution Single-Core Multi-Core CPU Core efficiency Software Acceleration Multimedia Gaming GPU
Putting all together – The Future is Fusion AMD “Istambul” six-core processor RV500 GPU Core (2006) 1 2 3 4 5 6 Ring L2 L2 L2 L2 L2 L2 Stop Client Interface Client Interface Cache L3 Client Interface Client Interface CROSSBAR Ring Memory Ring Stop Controller Stop Hyper Memory Client Interface Transport Controller Client Interface Client Interface Client Interface HyperTransport Ring Stop PCI-e Chipset
Putting all together – The Future is Fusion AMD “Istambul” six-core processor RV700 GPU Core (2008-2009) 1 2 3 4 5 6 L2 L2 L2 L2 L2 L2 Cache L3 CROSSBAR Hyper Memory Transport Controller HyperTransport PCI-e Chipset
Putting all together – The Future is Fusion AMD “Istambul” six-core processor RV700 GPU Core CROSSBAR CROSSBAR
2011: welcome to the APU time! CPU APU GPU “Supercomputing power in a notebook platform whose battery lasts for a full day”
One Design, Fewer Watts, Massive Capability “Zacate” Discrete-level AMD Dual-Core Northbridge + CPU + DirectX® 11 GPU = Fusion APU  66 sq. mm  117 sq. mm  59 sq. mm  75 sq. mm  13 watts  25 watts  8 watts  18 watts
Graphics and Media Processing Efficiency Improvements 2010 IGP-based Platform 2011 APU-based Platform ~17 GB/sec ~17 GB/sec CPU Cores DDR3 DIMM CPU Memory UNB / MC Cores CPU Chip DDR3 DIMM APU Chip MC Memory UVD UNB GPU ~27 GB/sec ~7 GB/sec Graphics requires GPU UVD memory bandwidth ~27 GB/sec PCIe to bring full SB Functions capabilities to life  3X bandwidth between GPU and memory  Even the same sized GPU is substantially more effective in this configuration PCIe  Eliminate latency and power associated with the extra chip crossing Bandwidth pinch points and latency  Substantially smaller physical foot print hold back the GPU capabilities
“Ontario” & “Zacate” Architecture APU >2 x86 CPU Cores (40nm “Bobcat” core – 1 MB L2, 64-bit FPU) >C6 and power gating >Array of SIMD Engines • DX11 graphics performance • Industry leading 3D and graphics processing >3rd Generation Unified Video Decoder >H.264, VC1, DixX/Xvid format >DDR3 800-1066, 2 DIMMs, 64 bit channel >BGA package Display and I/O >Two dedicated digital display interfaces • Configurable externally as HDMI, DVI, and/or Display Port • Also supports a single link LVDS for internal panels >Integrated VGA >5x8 PCIe® > “Hudson” Fusion Controller Hub
OpenCL Working together
ATI Stream SDK: OpenCL™ For Multicore x86 CPUs and GPUs http://developer.amd.com/ The Power of Fusion: Developers leverage heterogeneous architecture to deliver superior user experience • First complete OpenCL™ development platform • Certified OpenCL 1.0 compliant by the Khronos Group • Write code that can scale well on multi-core CPUs and GPUs • AMD delivers on the promise of OpenCL™, with both high- performance CPU and GPU technologies • Available for download now as part of ATI Stream SDK beta program – includes documentation, samples, and developer support
OpenCL™: Game-Changing Development Enabling Broad Adoption of GP-GPU Capabilities  Industry standard API: Open, multiplatform development platform for heterogeneous architectures  The power of Fusion: Leverages CPUs and GPUs for balanced system approach  Broad industry support: Created by architects from AMD, Apple, IBM, Intel, Nvidia, Sony, etc.  Fast track development: Ratified in December; AMD is the first company to provide a complete OpenCL solution  Momentum: Enormous interest from mainstream developers and application ISVs More stream-enabled applications across all markets
Open Standards: Maximize Developer Freedom and Addressable Market Vendor specific Vendor neutral Cross-platform limiters Cross-platform enablers • Apple Display Connector • 3dfx Glide Digital Visual OpenCL™ DirectX® Interface • Nvidia CUDA • Nvidia Cg • Rambus Certified DP JEDEC OpenGL® • Unified Display Interface
Comparing OpenCL™ and DirectX® 11 DirectCompute How will developers choose between OpenCL™ and DirectX® 11 DirectCompute?  Feature set is similar in both APIs DirectX® 11 DirectCompute  Easiest path to add compute capabilities to existing DirectX applications  Windows Vista® and Windows® 7 only OpenCL™  Ideal path for new applications porting to the GPU for the first time  True multiplatform: Windows®, Linux®, MacOS  Natural programming without dealing with a graphics API
Anatomy of OpenCL™ Language Specification • C-based cross-platform programming interface • Subset of ISO C99 with language extensions - familiar to developers • Well-defined numerical accuracy - IEEE 754 rounding behavior with defined maximum error • Online or offline compilation and build of compute kernel executables • Includes a rich set of built-in functions Platform Layer API • A hardware abstraction layer over diverse computational resources • Query, select and initialize compute devices • Create compute contexts and work-queues Runtime API • Execute compute kernels • Manage scheduling, compute, and memory resources
OpenCL Example Scalar void square(int n, const float *a, float *result) { int i; for (i=0; i<n; i++) result[i] = a[i] * a[i]; } Data-Parallel kernel dp_square (const float *a, float *result) { int id = get_global_id(0); result[id] = a[id] * a[id]; } // dp_square executes oven “n” work-items
Summary X86 PROCESSOR EVOLUTION THE GPU AS AN ACCELERATOR ACCELERATED PROCESSING UNITS INTRODUCTION TO OpenCL http://developer.amd.com 46
Obrigado! roberto.brandao@amd.com
roberto.brandao@amd.com Obrigado!

More Related Content

Amd accelerated computing -ufrj

  • 2. Agenda X86 PROCESSOR EVOLUTION THE GPU AS AN ACCELERATOR ACCELERATED PROCESSING UNITS INTRODUCTION TO OpenCL
  • 4. AMD architecture “Istambul” six-core diagram 1 2 3 4 5 6 Balanced Native caches L2 L2 L2 L2 L2 L2 six-core processor L3 Cache Lower memory latency CROSSBAR Hyper Memory Transport Controller HyperTransport PCI-e Fast full-duplex Chipset bus
  • 5. 4P/24-core system example very good scalability One memory controller for every MEMORY MEMORY processor Full-duplex Hyper Transport links (up to 5.2GHz) MEMORY MEMORY Bus Optimization: HT Assist (Cache Probe Filtering) Still the only available 4P system with Direct Connect Architecture
  • 6. Direct Connect Architecture 1.0 Balanced and Scalable Design to Support up to 6 Cores CHANNELS 2 MEMORY 2 MEMORY CHANNELS 8 DIMMs 8 DIMMs per CPU per CPU CHANNELS 2 MEMORY 2 MEMORY CHANNELS 8 DIMMs 8 DIMMs per CPU per CPU No front side bus HyperTransport™ technology Integrated memory controller NUMA memory architecture
  • 7. Direct Connect Architecture 2.0 Balanced and Scalable Design to Support up to 16 Cores* per CPU CHANNELS 4 MEMORY 4 MEMORY CHANNELS 12 DIMMs 12 DIMMs per CPU per CPU CHANNELS 4 MEMORY 4 MEMORY CHANNELS 12 DIMMs 12 DIMMs per CPU per CPU • 1-hop between processors • Four memory channels • Up to 50% more DIMMs • Up to 33% increase in CPU to CPU communication speed±
  • 8. What is next for x86 CPUs • More processor cores to come (12, 16, 16 double cores) • More memory channels (improves memory bandwidth per core) • Improved IPC (8 per cycle is a target)
  • 9. Top500 list - beyond the petaflop Datacenters in the USA will spend more than $3 billion on energy in 2009
  • 10. 1997: X Garry Kasparov IBM Deep Blue
  • 11. The World’s Most Powerful GPU =
  • 12. 2011 GPU Architecture AMD Radeon™ HD 6900 Series Dual graphics engines New VLIW4 core architecture Up to 24 SIMD engines Up to 96 Texture Units Upgraded render back-ends  Improved anti-aliasing performance Fast 256-bit GDDR5 memory interface  Up to 5.5 Gbps New GPU compute features
  • 13. Designing very efficient GPUs Full load: 180W; Idle:27W 16 14.47 14 GFLOPS/W 12 GFLOPS/W GFLOPS/mm2 10 7.50 8 4.50 7.90 GFLOPS/mm2 6 2.01 2.21 4.56 4 1.07 2.24 2 0.42 1.06 0.92 0 Nov-05 Jan-06 Sep-07 Nov-07 Jun-08 Oct-09 ATI Radeon™ ATI Radeon™ ATI Radeon™ HD ATI Radeon™ HD ATI Radeon™ HD ATI Radeon™ HD X1800 XT X1900 XTX 2900 PRO 3870 4870 5870
  • 14. Old and New in High Performance Computing Old: Power is free, Transistors are expensive New: Power expensive, Transistors free (Can put more transistors on chip than can afford to turn on) Old: Multiplies are slow, Memory access is fast New: Multiplies fast, Memory slow (up 200 clocks to DRAM memory, 4 clocks for FP multiply) Old: Increasing Instruction Level Parallelism via compilers innovation New: Explicit thread and data parallelism must be exploited
  • 15. GPUs: more than just gaming Processing power – millions of operations per second Single Core 12 Dual Core 24 Quad Core 48 Hexa Core 72 12 Cores 144 2700 Radeon HD 5970 Both use GPUs Wii Sports - Golf Oil exploration platform - 2010 15
  • 16. DirectX® 11 Multi-Threading  Application, DirectX runtime, and DirectX driver can each run in separate threads  Tasks like loading a texture or compiling a shader can execute in parallel with main rendering thread DirectX® 10 DirectX® 11 16
  • 17. Today’s GPUs focused on GAMING ENTERTAINMENT PRODUCTIVITY
  • 18. DirectX® 11 Tessellation DirectX® 10 DirectX® 11 No Tessellation Tessellation Images courtesy of Unigine Corp. 18
  • 21. Research companies already using Oil exploration Wheather forecast Fluid Dynamics Nature simulation 21
  • 22. AMD Balanced Platform GPU is ideal for data parallel algorithms CPU is excellent for running some like image processing, CAE, etc algorithms  Great use for ATI Stream  Ideal place to process if GPU is technology fully loaded  Great use for additional GPUs  Great use for additional CPU cores Graphics Workloads Serial/Task-Parallel Other Highly Workloads Parallel Workloads Delivers optimal performance for a wide range of platform configurations
  • 23. ATI Stream Technology is… Heterogeneous: Developers leverage AMD GPUs and x86 CPUs for optimal application performance and user experience High performance: Massively parallel, programmable GPU architecture delivers unprecedented performance and power efficiency Industry Standards: OpenCL™ and DirectCompute 11 enable cross-platform development Sciences Government Engineering Gaming Digital Productivity Content Creation
  • 24. Improvements already reached consumers 80% 70% 60% 50% ATI Stream 40% 30% 20% 10% 0% Processor utilization Adobe Flash plugin used by Youtube.com  Better image quality and video smoothness  Lower processor usage
  • 25. GPU-accelerated video transcoding Ipod Video HD Video Up to 6x faster when using an AMD graphics card
  • 26. Video Transcoding Sample No GPU Acceleration CPU Usage: 100% Using four CPU Cores GPU Usage: 1% CPU Usage: 100% Time to finish: 1h 52m Total Power: 0.23kW/h GPU Usage: 1% Peak power: 145W Energy Price: $0.15 26
  • 27. Video Transcoding Sample ATI GPU Acceleration CPU Usage: 45% GPU Usage: 35% Using hundreds of Stream Processors CPU Usage: 45% (100%) Time to finish: 26m (1h52m) Total Power: 0.11kW/h (0.23) GPU Usage: 35% (1%) Peak power: 198W (145W) Energy Price: $0.07 ($0.15) 27
  • 29. Today Multi-core CPU TeraFLOPS-class GPU ~800 million transistors Up to 2 billion transistors Multi-tasking Jogos em multiplos monitores Video e audio Full HD
  • 30. A new Era on performance evolution Heterogeneous Single-Core Multi-Core computing Challenge: Challenge: Pros: Power consumption Power consumption  Performance Complexity Software  Power efficient Cons: Software availability Single-thread Performance Performance ? We are here We are here We are here Time Time x Cores Time
  • 31. A new Era on performance evolution Single-Core Multi-Core CPU Core efficiency Software Acceleration Multimedia Gaming GPU
  • 32. Putting all together – The Future is Fusion AMD “Istambul” six-core processor RV500 GPU Core (2006) 1 2 3 4 5 6 Ring L2 L2 L2 L2 L2 L2 Stop Client Interface Client Interface Cache L3 Client Interface Client Interface CROSSBAR Ring Memory Ring Stop Controller Stop Hyper Memory Client Interface Transport Controller Client Interface Client Interface Client Interface HyperTransport Ring Stop PCI-e Chipset
  • 33. Putting all together – The Future is Fusion AMD “Istambul” six-core processor RV700 GPU Core (2008-2009) 1 2 3 4 5 6 L2 L2 L2 L2 L2 L2 Cache L3 CROSSBAR Hyper Memory Transport Controller HyperTransport PCI-e Chipset
  • 34. Putting all together – The Future is Fusion AMD “Istambul” six-core processor RV700 GPU Core CROSSBAR CROSSBAR
  • 35. 2011: welcome to the APU time! CPU APU GPU “Supercomputing power in a notebook platform whose battery lasts for a full day”
  • 36. One Design, Fewer Watts, Massive Capability “Zacate” Discrete-level AMD Dual-Core Northbridge + CPU + DirectX® 11 GPU = Fusion APU  66 sq. mm  117 sq. mm  59 sq. mm  75 sq. mm  13 watts  25 watts  8 watts  18 watts
  • 37. Graphics and Media Processing Efficiency Improvements 2010 IGP-based Platform 2011 APU-based Platform ~17 GB/sec ~17 GB/sec CPU Cores DDR3 DIMM CPU Memory UNB / MC Cores CPU Chip DDR3 DIMM APU Chip MC Memory UVD UNB GPU ~27 GB/sec ~7 GB/sec Graphics requires GPU UVD memory bandwidth ~27 GB/sec PCIe to bring full SB Functions capabilities to life  3X bandwidth between GPU and memory  Even the same sized GPU is substantially more effective in this configuration PCIe  Eliminate latency and power associated with the extra chip crossing Bandwidth pinch points and latency  Substantially smaller physical foot print hold back the GPU capabilities
  • 38. “Ontario” & “Zacate” Architecture APU >2 x86 CPU Cores (40nm “Bobcat” core – 1 MB L2, 64-bit FPU) >C6 and power gating >Array of SIMD Engines • DX11 graphics performance • Industry leading 3D and graphics processing >3rd Generation Unified Video Decoder >H.264, VC1, DixX/Xvid format >DDR3 800-1066, 2 DIMMs, 64 bit channel >BGA package Display and I/O >Two dedicated digital display interfaces • Configurable externally as HDMI, DVI, and/or Display Port • Also supports a single link LVDS for internal panels >Integrated VGA >5x8 PCIe® > “Hudson” Fusion Controller Hub
  • 40. ATI Stream SDK: OpenCL™ For Multicore x86 CPUs and GPUs http://developer.amd.com/ The Power of Fusion: Developers leverage heterogeneous architecture to deliver superior user experience • First complete OpenCL™ development platform • Certified OpenCL 1.0 compliant by the Khronos Group • Write code that can scale well on multi-core CPUs and GPUs • AMD delivers on the promise of OpenCL™, with both high- performance CPU and GPU technologies • Available for download now as part of ATI Stream SDK beta program – includes documentation, samples, and developer support
  • 41. OpenCL™: Game-Changing Development Enabling Broad Adoption of GP-GPU Capabilities  Industry standard API: Open, multiplatform development platform for heterogeneous architectures  The power of Fusion: Leverages CPUs and GPUs for balanced system approach  Broad industry support: Created by architects from AMD, Apple, IBM, Intel, Nvidia, Sony, etc.  Fast track development: Ratified in December; AMD is the first company to provide a complete OpenCL solution  Momentum: Enormous interest from mainstream developers and application ISVs More stream-enabled applications across all markets
  • 42. Open Standards: Maximize Developer Freedom and Addressable Market Vendor specific Vendor neutral Cross-platform limiters Cross-platform enablers • Apple Display Connector • 3dfx Glide Digital Visual OpenCL™ DirectX® Interface • Nvidia CUDA • Nvidia Cg • Rambus Certified DP JEDEC OpenGL® • Unified Display Interface
  • 43. Comparing OpenCL™ and DirectX® 11 DirectCompute How will developers choose between OpenCL™ and DirectX® 11 DirectCompute?  Feature set is similar in both APIs DirectX® 11 DirectCompute  Easiest path to add compute capabilities to existing DirectX applications  Windows Vista® and Windows® 7 only OpenCL™  Ideal path for new applications porting to the GPU for the first time  True multiplatform: Windows®, Linux®, MacOS  Natural programming without dealing with a graphics API
  • 44. Anatomy of OpenCL™ Language Specification • C-based cross-platform programming interface • Subset of ISO C99 with language extensions - familiar to developers • Well-defined numerical accuracy - IEEE 754 rounding behavior with defined maximum error • Online or offline compilation and build of compute kernel executables • Includes a rich set of built-in functions Platform Layer API • A hardware abstraction layer over diverse computational resources • Query, select and initialize compute devices • Create compute contexts and work-queues Runtime API • Execute compute kernels • Manage scheduling, compute, and memory resources
  • 45. OpenCL Example Scalar void square(int n, const float *a, float *result) { int i; for (i=0; i<n; i++) result[i] = a[i] * a[i]; } Data-Parallel kernel dp_square (const float *a, float *result) { int id = get_global_id(0); result[id] = a[id] * a[id]; } // dp_square executes oven “n” work-items
  • 46. Summary X86 PROCESSOR EVOLUTION THE GPU AS AN ACCELERATOR ACCELERATED PROCESSING UNITS INTRODUCTION TO OpenCL http://developer.amd.com 46