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i#3203: Add a basic last-level cache (LLC) miss analyzer (#3205)
The analyzer first identifies load instructions that suffer from significant last-level cache (LLC) misses. The analyzer then analyzes the cache line address streams for each of those load instructions in search for patterns that can be used for SW prefetching. The analyzer here can only find simple strides. Analyses for more complex patterns can be added in the future. A subsequent PR will connect the changes here to the front-end via new runtime options. Issue #3203
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| Original file line number | Diff line number | Diff line change |
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| /* ********************************************************** | ||
| * Copyright (c) 2015-2018 Google, LLC All rights reserved. | ||
| * **********************************************************/ | ||
|
|
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| /* | ||
| * Redistribution and use in source and binary forms, with or without | ||
| * modification, are permitted provided that the following conditions are met: | ||
| * | ||
| * * Redistributions of source code must retain the above copyright notice, | ||
| * this list of conditions and the following disclaimer. | ||
| * | ||
| * * Redistributions in binary form must reproduce the above copyright notice, | ||
| * this list of conditions and the following disclaimer in the documentation | ||
| * and/or other materials provided with the distribution. | ||
| * | ||
| * * Neither the name of Google, Inc. nor the names of its contributors may be | ||
| * used to endorse or promote products derived from this software without | ||
| * specific prior written permission. | ||
| * | ||
| * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | ||
| * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | ||
| * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE | ||
| * ARE DISCLAIMED. IN NO EVENT SHALL GOOGLE, LLC OR CONTRIBUTORS BE LIABLE | ||
| * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL | ||
| * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR | ||
| * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER | ||
| * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT | ||
| * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY | ||
| * OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH | ||
| * DAMAGE. | ||
| */ | ||
|
|
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| #include "cache_miss_analyzer.h" | ||
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| #include <stdint.h> | ||
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| const char *cache_miss_stats_t::kNTA = "nta"; | ||
| const char *cache_miss_stats_t::kT0 = "t0"; | ||
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| analysis_tool_t * | ||
| cache_miss_analyzer_create(const cache_simulator_knobs_t &knobs, | ||
| unsigned int miss_count_threshold, double miss_frac_threshold, | ||
| double confidence_threshold) | ||
| { | ||
| return new cache_miss_analyzer_t(knobs, miss_count_threshold, miss_frac_threshold, | ||
| confidence_threshold); | ||
| } | ||
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| cache_miss_stats_t::cache_miss_stats_t(bool warmup_enabled, unsigned int line_size, | ||
| unsigned int miss_count_threshold, | ||
| double miss_frac_threshold, | ||
| double confidence_threshold) | ||
| : cache_stats_t("", warmup_enabled) | ||
| , kLineSize(line_size) | ||
| , kMissCountThreshold(miss_count_threshold) | ||
| , kMissFracThreshold(miss_frac_threshold) | ||
| , kConfidenceThreshold(confidence_threshold) | ||
| { | ||
| // Setting this variable to true ensures that the dump_miss() function below | ||
| // gets called during cache simulation on a cache miss. | ||
| dump_misses = true; | ||
| } | ||
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| void | ||
| cache_miss_stats_t::reset() | ||
| { | ||
| cache_stats_t::reset(); | ||
| pc_cache_misses.clear(); | ||
| total_misses = 0; | ||
| } | ||
|
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| void | ||
| cache_miss_stats_t::dump_miss(const memref_t &memref) | ||
| { | ||
| // If the operation causing the LLC miss is a memory read (load), insert | ||
| // the miss into the pc_cache_misses hash map and update | ||
| // the total_misses counter. | ||
| if (memref.data.type != TRACE_TYPE_READ) { | ||
| return; | ||
| } | ||
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| const addr_t pc = memref.data.pc; | ||
| const addr_t addr = memref.data.addr / kLineSize; | ||
| pc_cache_misses[pc].push_back(addr); | ||
| total_misses++; | ||
| } | ||
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| std::vector<prefetching_recommendation_t *> | ||
| cache_miss_stats_t::generate_recommendations() | ||
| { | ||
| unsigned int miss_count_threshold = | ||
| static_cast<unsigned int>(kMissFracThreshold * total_misses); | ||
| if (miss_count_threshold > kMissCountThreshold) { | ||
| miss_count_threshold = kMissCountThreshold; | ||
| } | ||
|
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| // Find loads that should be analyzed and analyze them. | ||
| std::vector<prefetching_recommendation_t *> recommendations; | ||
| for (auto &pc_cache_misses_it : pc_cache_misses) { | ||
| std::vector<addr_t> &cache_misses = pc_cache_misses_it.second; | ||
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| if (cache_misses.size() >= miss_count_threshold) { | ||
| const int stride = check_for_constant_stride(cache_misses); | ||
| if (stride != 0) { | ||
| prefetching_recommendation_t *recommendation = | ||
| new prefetching_recommendation_t; | ||
| recommendation->pc = pc_cache_misses_it.first; | ||
| recommendation->stride = stride; | ||
| recommendation->locality = kNTA; | ||
| recommendations.push_back(recommendation); | ||
| } | ||
| } | ||
| } | ||
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| return recommendations; | ||
| } | ||
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| int | ||
| cache_miss_stats_t::check_for_constant_stride( | ||
| const std::vector<addr_t> &cache_misses) const | ||
| { | ||
| std::unordered_map<int, int> stride_counts; | ||
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| // Find and count all strides in the misses stream. | ||
| for (unsigned int i = 1; i < cache_misses.size(); ++i) { | ||
| int stride = static_cast<int>(cache_misses[i] - cache_misses[i - 1]); | ||
| if (stride != 0) { | ||
| stride_counts[stride]++; | ||
| } | ||
| } | ||
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| // Find the most occurring stride. | ||
| int max_count = 0; | ||
| int max_count_stride = 0; | ||
| for (auto &stride_count : stride_counts) { | ||
| if (stride_count.second > max_count) { | ||
| max_count = stride_count.second; | ||
| max_count_stride = stride_count.first; | ||
| } | ||
| } | ||
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| // Return the most occurring stride if it meets the confidence threshold. | ||
| stride_counts.clear(); | ||
| if (max_count >= static_cast<int>(kConfidenceThreshold * cache_misses.size())) { | ||
| return max_count_stride; | ||
| } else { | ||
| return 0; | ||
| } | ||
| } | ||
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| cache_miss_analyzer_t::cache_miss_analyzer_t(const cache_simulator_knobs_t &knobs, | ||
| unsigned int miss_count_threshold, | ||
| double miss_frac_threshold, | ||
| double confidence_threshold) | ||
| : cache_simulator_t(knobs) | ||
| { | ||
| if (!success) { | ||
| return; | ||
| } | ||
| bool warmup_enabled = (knobs.warmup_refs > 0 || knobs.warmup_fraction > 0.0); | ||
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| delete llcaches["LL"]->get_stats(); | ||
| ll_stats = | ||
| new cache_miss_stats_t(warmup_enabled, knobs.line_size, miss_count_threshold, | ||
| miss_frac_threshold, confidence_threshold); | ||
| llcaches["LL"]->set_stats(ll_stats); | ||
| } | ||
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| std::vector<prefetching_recommendation_t *> | ||
| cache_miss_analyzer_t::generate_recommendations() | ||
| { | ||
| return ll_stats->generate_recommendations(); | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,154 @@ | ||
| /* ********************************************************** | ||
| * Copyright (c) 2015-2018 Google, LLC All rights reserved. | ||
| * **********************************************************/ | ||
|
|
||
| /* | ||
| * Redistribution and use in source and binary forms, with or without | ||
| * modification, are permitted provided that the following conditions are met: | ||
| * | ||
| * * Redistributions of source code must retain the above copyright notice, | ||
| * this list of conditions and the following disclaimer. | ||
| * | ||
| * * Redistributions in binary form must reproduce the above copyright notice, | ||
| * this list of conditions and the following disclaimer in the documentation | ||
| * and/or other materials provided with the distribution. | ||
| * | ||
| * * Neither the name of Google, Inc. nor the names of its contributors may be | ||
| * used to endorse or promote products derived from this software without | ||
| * specific prior written permission. | ||
| * | ||
| * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | ||
| * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | ||
| * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE | ||
| * ARE DISCLAIMED. IN NO EVENT SHALL GOOGLE, LLC OR CONTRIBUTORS BE LIABLE | ||
| * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL | ||
| * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR | ||
| * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER | ||
| * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT | ||
| * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY | ||
| * OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH | ||
| * DAMAGE. | ||
| */ | ||
|
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| /* cache_miss_analyzer: finds the load instructions suffering from | ||
| * a significant number of last-level cache (LLC) misses. In addition, | ||
| * it analyzes the data memory addresses accessed by these load instructions | ||
| * and identifies patterns that can be used in SW prefetching. | ||
| */ | ||
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| #ifndef _CACHE_MISS_ANALYZER_H_ | ||
| #define _CACHE_MISS_ANALYZER_H_ 1 | ||
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| #include <cstdint> | ||
| #include <string> | ||
| #include <unordered_map> | ||
| #include <vector> | ||
|
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| #include "cache_simulator.h" | ||
| #include "cache_stats.h" | ||
| #include "../common/memref.h" | ||
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| // Represents the SW prefetching recommendation passed to the compiler. | ||
| struct prefetching_recommendation_t { | ||
| addr_t pc; // Load instruction's address. | ||
| int stride; // Prefetching stride/delta distance. | ||
| std::string locality; // Prefetching locality: one of "nta" or "t0". | ||
| }; | ||
|
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| class cache_miss_stats_t : public cache_stats_t { | ||
| public: | ||
| // Constructor - params description: | ||
| // - warmup_enabled: Indicates whether the caches need to be warmed up | ||
| // before stats and misses start being collected. | ||
| // - line_size: The cache line size in bytes. | ||
| // - miss_count_threshold: Threshold of misses count by a load instruction | ||
| // to be eligible for analysis. | ||
| // - miss_frac_threshold: Threshold of misses fraction by a load | ||
| // instruction to be eligible for analysis. | ||
| // - confidence_threshold: Confidence threshold to include a discovered | ||
| // pattern in the output results. | ||
| // Confidence in a discovered pattern for a load instruction is calculated | ||
| // as the fraction of the load's misses with the discovered pattern over | ||
| // all the load's misses. | ||
| cache_miss_stats_t(bool warmup_enabled = false, unsigned int line_size = 64, | ||
| unsigned int miss_count_threshold = 50000, | ||
| double miss_frac_threshold = 0.005, | ||
| double confidence_threshold = 0.75); | ||
|
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| cache_miss_stats_t & | ||
| operator=(const cache_miss_stats_t &) | ||
| { | ||
| return *this; | ||
| } | ||
|
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| virtual void | ||
| reset(); | ||
|
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| std::vector<prefetching_recommendation_t *> | ||
| generate_recommendations(); | ||
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| protected: | ||
| virtual void | ||
| dump_miss(const memref_t &memref); | ||
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| private: | ||
| // Two locality levels for prefetching are supported: nta and t0. | ||
| static const char *kNTA; | ||
| static const char *kT0; | ||
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| // Cache line size. | ||
| const unsigned int kLineSize; | ||
|
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| // A load instruction should be analyzed if its total number/fraction of LLC | ||
| // misses is equal to or larger than one of the two threshold values below: | ||
| const unsigned int kMissCountThreshold; // Absolute count. | ||
| const double kMissFracThreshold; // Fraction of all LLC misses. | ||
|
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| // Confidence threshold for recording a cache misses stride. | ||
| // Confidence in a discovered pattern for a load instruction is calculated | ||
| // as the fraction of the load's misses with the discovered pattern over | ||
| // all the load's misses. | ||
| const double kConfidenceThreshold; | ||
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| // A function to analyze cache misses in search of a constant stride. | ||
| // The function returns a nonzero stride value if it finds one that | ||
| // satisfies the confidence threshold and returns 0 otherwise. | ||
| int | ||
| check_for_constant_stride(const std::vector<addr_t> &cache_misses) const; | ||
|
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| // A hash map storing the data cache line addresses accessed by load | ||
| // instructions that miss in the LLC. | ||
| // Key is the PC of the load instruction. | ||
| // Value is a vector of data memory cache line addresses. | ||
| std::unordered_map<addr_t, std::vector<addr_t>> pc_cache_misses; | ||
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| // Total number of LLC misses added to the hash map above. | ||
| int total_misses = 0; | ||
| }; | ||
|
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| class cache_miss_analyzer_t : public cache_simulator_t { | ||
| public: | ||
| // Constructor: | ||
| // - cache_simulator_knobs_t: Encapsulates the cache simulator params. | ||
| // - miss_count_threshold: Threshold of miss count by a load instruction | ||
| // to be eligible for analysis. | ||
| // - miss_frac_threshold: Threshold of miss fraction by a load | ||
| // instruction to be eligible for analysis. | ||
| // - confidence_threshold: Confidence threshold to include a discovered | ||
| // pattern in the output results. | ||
| // Confidence in a discovered pattern for a load instruction is calculated | ||
| // as the fraction of the load's misses with the discovered pattern over | ||
| // all the load's misses. | ||
| cache_miss_analyzer_t(const cache_simulator_knobs_t &knobs, | ||
| unsigned int miss_count_threshold = 50000, | ||
| double miss_frac_threshold = 0.005, | ||
| double confidence_threshold = 0.75); | ||
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| std::vector<prefetching_recommendation_t *> | ||
| generate_recommendations(); | ||
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| private: | ||
| cache_miss_stats_t *ll_stats; | ||
| }; | ||
|
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| #endif /* _CACHE_MISS_ANALYZER_H_ */ |
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