73b193aec2
Add a header-only implementation of Briggs & Torczon's fast small integer set data structure to flang/include/flang/Common, and use it in the runtime to manage a pool of Fortran unit numbers with recycling. This replaces the bit set previously used for that purpose. The set is initialized on demand with the negations of all the NEWUNIT= unit numbers that can be returned to any kind of integer variable. For programs that require more concurrently open NEWUNIT= unit numbers than the pool can hold, they are now allocated with a non-recycling counter. This allows as many open units as the operating system provides. Many of the top-line comments in flang/unittests/Runtime had the wrong path name. I noticed this while adding a unit test for the fast integer set data structure, and cleaned them up. Differential Revision: https://reviews.llvm.org/D120685
64 lines
2.2 KiB
C++
64 lines
2.2 KiB
C++
//===-- flang/unittests/Runtime/Random.cpp ----------------------*- C++ -*-===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#include "flang/Runtime//random.h"
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#include "gtest/gtest.h"
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#include "flang/Runtime/descriptor.h"
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#include "flang/Runtime/type-code.h"
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#include <cmath>
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using namespace Fortran::runtime;
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TEST(RandomNumber, Real4) {
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StaticDescriptor<1> statDesc;
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Descriptor &harvest{statDesc.descriptor()};
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static constexpr int n{10000};
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float xs[n]{};
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SubscriptValue extent[1]{n};
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harvest.Establish(TypeCategory::Real, 4, xs, 1, extent);
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RTNAME(RandomNumber)(harvest, __FILE__, __LINE__);
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double sum{0};
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for (int j{0}; j < n; ++j) {
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sum += xs[j];
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}
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double mean{sum / n};
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std::fprintf(stderr, "mean of %d random numbers: %g\n", n, mean);
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EXPECT_GE(mean, 0.95 * 0.5); // mean of uniform dist [0..1] is of course 0.5
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EXPECT_LE(mean, 1.05 * 0.5);
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double sumsq{0};
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for (int j{0}; j < n; ++j) {
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double diff{xs[j] - mean};
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sumsq += diff * diff;
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}
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double sdev{std::sqrt(sumsq / n)};
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std::fprintf(stderr, "stddev of %d random numbers: %g\n", n, sdev);
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double expect{1.0 / std::sqrt(12.0)}; // stddev of uniform dist [0..1]
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EXPECT_GE(sdev, 0.95 * expect);
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EXPECT_LT(sdev, 1.05 * expect);
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}
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TEST(RandomNumber, RandomSeed) {
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StaticDescriptor<1> statDesc[2];
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Descriptor &desc{statDesc[0].descriptor()};
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std::int32_t n;
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desc.Establish(TypeCategory::Integer, 4, &n, 0, nullptr);
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RTNAME(RandomSeedSize)(desc, __FILE__, __LINE__);
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EXPECT_EQ(n, 1);
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SubscriptValue extent[1]{1};
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desc.Establish(TypeCategory::Integer, 4, &n, 1, extent);
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RTNAME(RandomSeedGet)(desc, __FILE__, __LINE__);
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Descriptor &harvest{statDesc[1].descriptor()};
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float x;
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harvest.Establish(TypeCategory::Real, 4, &x, 1, extent);
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RTNAME(RandomNumber)(harvest, __FILE__, __LINE__);
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float got{x};
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RTNAME(RandomSeedPut)(desc, __FILE__, __LINE__); // n from RandomSeedGet()
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RTNAME(RandomNumber)(harvest, __FILE__, __LINE__);
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EXPECT_EQ(x, got);
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}
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