Intel® FPGA SDK for OpenCL™ Standard Edition: Best Practices Guide

ID 683176
Date 9/24/2018
Document Table of Contents

7.2.1. Contiguous Memory Accesses

Contiguous memory access optimizations analyze statically the access patterns of global load and store operations in a kernel. For sequential load or store operations that occur for the entire kernel invocation, the directs the kernel to access consecutive locations in global memory.

Consider the following code example:

__kernel void sum ( __global const float * restrict a,
                    __global const float * restrict b,
                    __global float * restrict c )
	size_t gid = get_global_id(0);

	c[gid] = a[gid] + b[gid];

The load operation from array a uses an index that is a direct function of the work-item global ID. By basing the array index on the work-item global ID, the offline compiler can direct contiguous load operations. These load operations retrieve the data sequentially from the input array, and sends the read data to the pipeline as required. Contiguous store operations then store elements of the result that exits the computation pipeline in sequential locations within global memory.

Tip: Use the const qualifier for any read-only global buffer so that the offline compiler can perform more aggressive optimizations on the load operation.

The following figure illustrates an example of the contiguous memory access optimization:

Figure 79. Contiguous Memory Access

Contiguous load and store operations improve memory access efficiency because they lead to increased access speeds and reduced hardware resource needs. The data travels in and out of the computational portion of the pipeline concurrently, allowing overlaps between computation and memory accesses. If possible, use work-item IDs that index consecutive memory locations for load and store operations that access global memory. Sequential accesses to global memory increase memory efficiency because they provide an ideal access pattern.