Strip-mining, also known as loop sectioning, is a loop transformation technique for enabling SIMD-encodings of loops, as well as a means of improving memory performance. By fragmenting a large loop into smaller segments or strips, this technique transforms the loop structure in two ways:
It increases the temporal and spatial locality in the data cache if the data are reusable in different passes of an algorithm.
It reduces the number of iterations of the loop by a factor of the length of each vector, or number of operations being performed per SIMD operation. In the case of Streaming SIMD Extensions, this vector or strip-length is reduced by 4 times: four floating-point data items per single Streaming SIMD Extensions single-precision floating-point SIMD operation are processed.
First introduced for vectorizers, this technique consists of the generation of code when each vector operation is done for a size less than or equal to the maximum vector length on a given vector machine.
The compiler automatically strip-mines your loop and generates a cleanup loop. The following examples demonstrate strip mining and cleaning up loops.
Example1: Before Vectorization |
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i = 1 |
Example 2: After Vectorization |
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!The vectorizer generates the following two loops |
It is possible to treat loop blocking as strip-mining in two or more dimensions. Loop blocking is a useful technique for memory performance optimization. The main purpose of loop blocking is to eliminate as many cache misses as possible. This technique transforms the memory domain into smaller chunks rather than sequentially traversing through the entire memory domain. Each chunk should be small enough to fit all the data for a given computation into the cache, thereby maximizing data reuse.
Consider the following example. The two-dimensional array A is referenced in the j (column) direction and then in the i (row) direction (column-major order); array B is referenced in the opposite manner (row-major order). Assume the memory layout is in column-major order; therefore, the access strides of array A and B for the code would be 1 and MAX, respectively.
In example 2: BS = block_size; MAX must be evenly divisible by BS.
The following examples demonstrate loop blocking of arrays.
Example 3: Original loop |
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REAL A(MAX,MAX), B(MAX,MAX) DO I =1, MAX |
Example 4: Transformed Loop after blocking |
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REAL A(MAX,MAX), B(MAX,MAX) |