Product Discontinuance Notification 1. Introduction to Intel® FPGA SDK for OpenCL™ Pro Edition Best Practices Guide 2. Reviewing Your Kernel's report.html File 3. OpenCL Kernel Design Concepts 4. OpenCL Kernel Design Best Practices 5. Profiling Your Kernel to Identify Performance Bottlenecks 6. Strategies for Improving Single Work-Item Kernel Performance 7. Strategies for Improving NDRange Kernel Data Processing Efficiency 8. Strategies for Improving Memory Access Efficiency 9. Strategies for Optimizing FPGA Area Usage 10. Strategies for Optimizing Intel® Stratix® 10 OpenCL Designs 11. Strategies for Improving Performance in Your Host Application 12. Intel® FPGA SDK for OpenCL™ Pro Edition Best Practices Guide Archives A. Document Revision History for the Intel® FPGA SDK for OpenCL™ Pro Edition Best Practices Guide
2.1. High-Level Design Report Layout 2.2. Reviewing the Summary Report 2.3. Viewing Throughput Bottlenecks in the Design 2.4. Using Views 2.5. Analyzing Throughput 2.6. Reviewing Area Information 2.7. Optimizing an OpenCL Design Example Based on Information in the HTML Report 2.8. Accessing HLD FPGA Reports in JSON Format
4.1. Transferring Data Via Intel® FPGA SDK for OpenCL™ Channels or OpenCL Pipes 4.2. Unrolling Loops 4.3. Optimizing Floating-Point Operations 4.4. Allocating Aligned Memory 4.5. Aligning a Struct with or without Padding 4.6. Maintaining Similar Structures for Vector Type Elements 4.7. Avoiding Pointer Aliasing 4.8. Avoid Expensive Functions 4.9. Avoiding Work-Item ID-Dependent Backward Branching
5.1. Best Practices for Profiling Your Kernel 5.2. Instrumenting the Kernel Pipeline with Performance Counters (-profile) 5.3. Obtaining Profiling Data During Runtime 5.4. Reducing Area Resource Use While Profiling 5.5. Temporal Performance Collection 5.6. Performance Data Types 5.7. Interpreting the Profiling Information 5.8. Profiler Analyses of Example OpenCL Design Scenarios 5.9. Intel® FPGA Dynamic Profiler for OpenCL™ Limitations
8.1. General Guidelines on Optimizing Memory Accesses 8.2. Optimize Global Memory Accesses 8.3. Performing Kernel Computations Using Constant, Local or Private Memory 8.4. Improving Kernel Performance by Banking the Local Memory 8.5. Optimizing Accesses to Local Memory by Controlling the Memory Replication Factor 8.6. Minimizing the Memory Dependencies for Loop Pipelining 8.7. Static Memory Coalescing
8.2.2. Manual Partitioning of Global Memory
You can partition the memory manually so that each buffer occupies a different memory bank.
The default burst-interleaved configuration of the global memory prevents load imbalance by ensuring that memory accesses do not favor one external memory bank over another. However, you have the option to control the memory bandwidth across a group of buffers by partitioning your data manually.
The Intel® FPGA SDK for OpenCL™ Offline Compiler cannot burst-interleave across different memory types. To manually partition a specific type of global memory , compile your OpenCL™ kernels with the -no-interleaving=<global_memory_type> flag to configure each bank of a certain memory type as non-interleaved banks.
If your kernel accesses two buffers of equal size in memory, you can distribute your data to both memory banks simultaneously regardless of dynamic scheduling between the loads. This optimization step might increase your apparent memory bandwidth.
If your kernel accesses heterogeneous global memory types, include the -no-interleaving=<global_memory_type> option in the aoc command for each memory type that you want to partition manually.
For more information about the usage of the -no-interleaving=<global_memory_type> option, refer to the Disabling Burst-Interleaving of Global Memory (-no-interleaving=<global_memory_type>) section of the Intel® FPGA SDK for OpenCL™ Programming Guide.
Heterogeneous Memory Buffers
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