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Details:
- Defined a new randomization operation, randn, on vectors and matrices.
The randnv and randnm operations randomize each element of the target
object with values from a narrow range of values. Presently, those
values are all integer powers of two, but they do not need to be powers
of two in order to achieve the primary goal, which is to initialize
objects that can be operated on with plenty of precision "slack"
available to allow computations that avoid roundoff. Using this method
of randomization makes it much more likely that testsuite residuals of
properly-functioning operations are close to zero, if not exactly zero.
- Updated existing randomization operations randv and randm to skip
special diagonal handling and normalization for matrices with structure.
This is now handled by the testsuite modules by explicitly calling a
testsuite function that loads the diagonal (and scales off-diagonal
elements).
- Added support for randnv and randnm in the testsuite with a new switch
in input.general that universally toggles between use of the classic
randv/randm, which use real values on the interval [-1,1], and
randnv/randnm, which use only values from a narrow range. Currently,
the narrow range is: +/-{2^0, 2^-1, 2^-2, 2^-3, 2^-4, 2^-5, 2^-6}, as
well as 0.0.
- Updated testsuite modules so that a testsutie wrapper function is called
instead of directly calling the randomization operations (such as
bli_randv() and bli_randm()). This wrapper also takes a bool_t that
indicates whether the object's elements should be normalized. (NOTE: As
alluded to above, in the test modules of triangular solve operations such
as trsv and trsm, we perform the extra step of loading the diagonal.)
- Defined a new level-0 operation, invertsc, which inverts a scalar.
- Updated the abval2ris and sqrt2ris level-0 macros to avoid an unlikely
but possible divide-by-zero.
- Updated function signature and prototype formatting in testsuite.
45 lines
2.0 KiB
Plaintext
45 lines
2.0 KiB
Plaintext
# ----------------------------------------------------------------------
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#
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# input.general
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# BLIS test suite
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#
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# This file contains input values that control how BLIS operations are
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# tested. Comments explain the purpose of each parameter as well as
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# accepted values.
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#
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1 # Number of repeats per experiment (best result is reported)
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c # Matrix storage scheme(s) to test:
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# 'c' = col-major storage; 'g' = general stride storage;
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# 'r' = row-major storage
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c # Vector storage scheme(s) to test:
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# 'c' = colvec / unit stride; 'j' = colvec / non-unit stride;
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# 'r' = rowvec / unit stride; 'i' = rowvec / non-unit stride
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0 # Test all combinations of storage schemes?
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1 # Perform all tests with alignment?
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# '0' = do NOT align buffers/ldims; '1' = align buffers/ldims
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0 # Randomize vectors and matrices using:
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# '0' = real values on [-1,1];
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# '1' = powers of 2 in narrow precision range
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32 # General stride spacing (for cases when testing general stride)
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sdcz # Datatype(s) to test:
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# 's' = single real; 'c' = single complex;
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# 'd' = double real; 'z' = double complex
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100 # Problem size: first to test
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400 # Problem size: maximum to test
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100 # Problem size: increment between experiments
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# Complex level-3 implementations to test
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1 # 3mh ('1' = enable; '0' = disable)
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1 # 3m3 ('1' = enable; '0' = disable)
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1 # 3m2 ('1' = enable; '0' = disable)
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1 # 3m1 ('1' = enable; '0' = disable)
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1 # 4mh ('1' = enable; '0' = disable)
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1 # 4m1b ('1' = enable; '0' = disable)
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1 # 4m1a ('1' = enable; '0' = disable)
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1 # Error-checking level:
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# '0' = disable error checking; '1' = full error checking
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i # Reaction to test failure:
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# 'i' = ignore; 's' = sleep() and continue; 'a' = abort
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0 # Output results in matlab/octave format? ('1' = yes; '0' = no)
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0 # Output results to stdout AND files? ('1' = yes; '0' = no)
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