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Python Parallel Programming Cookbook
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PyCUDA provides a functionality to perform reduction operations on the GPU. This is possible with the pycuda.reduction.ReductionKernel method:
ReductionKernel(dtype_out, arguments, map_expr ,reduce_expr,
name,optional_parameters) Here, we note that:
dtype_out: This is the output's data type. It must be specified by the numpy.dtype data type.
arguments: This is a C argument list of all the parameters involved in the reduction's operation.
map_expr: This is a string that represents the mapping operation. Each vector in this expression must be referenced with the variable i.
reduce_expr: This is a string that represents the reduction operation. The operands in this expression are indicated by lowercase letters, such as a, b, c, ..., z.
name: This is the name associated with ReductionKernel, with which the kernel is compiled.
optional_parameters: These are not important in this recipe as they are the compiler's directives.
The method executes...
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