153 lines
6.0 KiB
C++
153 lines
6.0 KiB
C++
/*
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* Copyright (c) 2018, Oracle and/or its affiliates. All rights reserved.
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* Copyright (c) 2018, Google and/or its affiliates. All rights reserved.
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* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
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*
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* This code is free software; you can redistribute it and/or modify it
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* under the terms of the GNU General Public License version 2 only, as
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* published by the Free Software Foundation.
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*
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* This code is distributed in the hope that it will be useful, but WITHOUT
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* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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* version 2 for more details (a copy is included in the LICENSE file that
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* accompanied this code).
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*
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* You should have received a copy of the GNU General Public License version
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* 2 along with this work; if not, write to the Free Software Foundation,
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* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
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*
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* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
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* or visit www.oracle.com if you need additional information or have any
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* questions.
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*
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*/
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#include "precompiled.hpp"
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#include "runtime/handles.inline.hpp"
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#include "runtime/orderAccess.hpp"
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#include "runtime/sharedRuntime.hpp"
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#include "runtime/threadHeapSampler.hpp"
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// Cheap random number generator.
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uint64_t ThreadHeapSampler::_rnd;
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// Default is 512kb.
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volatile int ThreadHeapSampler::_sampling_interval = 512 * 1024;
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// Ordering here is important: _log_table first, _log_table_initialized second.
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double ThreadHeapSampler::_log_table[1 << ThreadHeapSampler::FastLogNumBits] = {};
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// Force initialization of the log_table.
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bool ThreadHeapSampler::_log_table_initialized = init_log_table();
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bool ThreadHeapSampler::init_log_table() {
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for (int i = 0; i < (1 << FastLogNumBits); i++) {
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_log_table[i] = (log(1.0 + static_cast<double>(i+0.5) / (1 << FastLogNumBits))
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/ log(2.0));
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}
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return true;
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}
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// Returns the next prng value.
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// pRNG is: aX+b mod c with a = 0x5DEECE66D, b = 0xB, c = 1<<48
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// This is the lrand64 generator.
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uint64_t ThreadHeapSampler::next_random(uint64_t rnd) {
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const uint64_t PrngMult = 0x5DEECE66DLL;
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const uint64_t PrngAdd = 0xB;
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const uint64_t PrngModPower = 48;
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const uint64_t PrngModMask = ((uint64_t)1 << PrngModPower) - 1;
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//assert(IS_SAFE_SIZE_MUL(PrngMult, rnd), "Overflow on multiplication.");
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//assert(IS_SAFE_SIZE_ADD(PrngMult * rnd, PrngAdd), "Overflow on addition.");
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return (PrngMult * rnd + PrngAdd) & PrngModMask;
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}
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double ThreadHeapSampler::fast_log2(const double& d) {
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assert(d>0, "bad value passed to assert");
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uint64_t x = 0;
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assert(sizeof(d) == sizeof(x),
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"double and uint64_t do not have the same size");
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x = *reinterpret_cast<const uint64_t*>(&d);
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const uint32_t x_high = x >> 32;
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assert(FastLogNumBits <= 20, "FastLogNumBits should be less than 20.");
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const uint32_t y = x_high >> (20 - FastLogNumBits) & FastLogMask;
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const int32_t exponent = ((x_high >> 20) & 0x7FF) - 1023;
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assert(_log_table_initialized, "log table should be initialized");
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return exponent + _log_table[y];
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}
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// Generates a geometric variable with the specified mean (512K by default).
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// This is done by generating a random number between 0 and 1 and applying
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// the inverse cumulative distribution function for an exponential.
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// Specifically: Let m be the inverse of the sample interval, then
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// the probability distribution function is m*exp(-mx) so the CDF is
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// p = 1 - exp(-mx), so
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// q = 1 - p = exp(-mx)
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// log_e(q) = -mx
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// -log_e(q)/m = x
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// log_2(q) * (-log_e(2) * 1/m) = x
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// In the code, q is actually in the range 1 to 2**26, hence the -26 below
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void ThreadHeapSampler::pick_next_geometric_sample() {
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_rnd = next_random(_rnd);
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// Take the top 26 bits as the random number
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// (This plus a 1<<58 sampling bound gives a max possible step of
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// 5194297183973780480 bytes. In this case,
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// for sample_parameter = 1<<19, max possible step is
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// 9448372 bytes (24 bits).
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const uint64_t PrngModPower = 48; // Number of bits in prng
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// The uint32_t cast is to prevent a (hard-to-reproduce) NAN
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// under piii debug for some binaries.
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double q = static_cast<uint32_t>(_rnd >> (PrngModPower - 26)) + 1.0;
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// Put the computed p-value through the CDF of a geometric.
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// For faster performance (save ~1/20th exec time), replace
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// min(0.0, FastLog2(q) - 26) by (Fastlog2(q) - 26.000705)
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// The value 26.000705 is used rather than 26 to compensate
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// for inaccuracies in FastLog2 which otherwise result in a
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// negative answer.
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double log_val = (fast_log2(q) - 26);
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double result =
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(0.0 < log_val ? 0.0 : log_val) * (-log(2.0) * (get_sampling_interval())) + 1;
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assert(result > 0 && result < SIZE_MAX, "Result is not in an acceptable range.");
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size_t interval = static_cast<size_t>(result);
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_bytes_until_sample = interval;
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}
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void ThreadHeapSampler::pick_next_sample(size_t overflowed_bytes) {
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// Explicitly test if the sampling interval is 0, return 0 to sample every
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// allocation.
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if (get_sampling_interval() == 0) {
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_bytes_until_sample = 0;
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return;
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}
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pick_next_geometric_sample();
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// Try to correct sample size by removing extra space from last allocation.
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if (overflowed_bytes > 0 && _bytes_until_sample > overflowed_bytes) {
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_bytes_until_sample -= overflowed_bytes;
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}
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}
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void ThreadHeapSampler::check_for_sampling(oop obj, size_t allocation_size, size_t bytes_since_allocation) {
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size_t total_allocated_bytes = bytes_since_allocation + allocation_size;
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// If not yet time for a sample, skip it.
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if (total_allocated_bytes < _bytes_until_sample) {
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_bytes_until_sample -= total_allocated_bytes;
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return;
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}
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JvmtiExport::sampled_object_alloc_event_collector(obj);
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size_t overflow_bytes = total_allocated_bytes - _bytes_until_sample;
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pick_next_sample(overflow_bytes);
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}
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int ThreadHeapSampler::get_sampling_interval() {
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return OrderAccess::load_acquire(&_sampling_interval);
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}
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void ThreadHeapSampler::set_sampling_interval(int sampling_interval) {
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OrderAccess::release_store(&_sampling_interval, sampling_interval);
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}
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