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| -rw-r--r-- | src/benchmarks/larson.py | 38 |
1 files changed, 31 insertions, 7 deletions
diff --git a/src/benchmarks/larson.py b/src/benchmarks/larson.py index 0e6c91e..970b5f2 100644 --- a/src/benchmarks/larson.py +++ b/src/benchmarks/larson.py @@ -15,7 +15,36 @@ # You should have received a copy of the GNU General Public License # along with allocbench. If not, see <http://www.gnu.org/licenses/>. -"""Definition of the larson benchmark""" +"""Larson server benchmark + +This benchmark was build by Paul Larson at Microsoft Research. It +simulates a server: each thread has a set of allocations. From which it selects +a random slot. The allocation in this slot is freed, a new one with a random size +allocated, written to and stored in the selected slot. When a thread finished its +allocations it will pass its objects to a new thread. + +Larson benchmark usage: ./larson sleep min-size max-size chunks malloc_frees seed threads + +In the paper "Memory Allocation for Long-Running Server Applications" the authors +use 1000 chunks per thread and 50000 malloc and free pairs per thread which +correspond to a "bleeding rate" of 2% which they observed in real world systems. +The allocations are uniformly distributed between min-size and max-size. + +allocbench runs larson with different distributions and thread counts. +The other arguments are the same as the original authors used in their paper. + +mimalloc-bench uses 1000 chunks per thread and 10000 malloc and free pairs +simulating 10% bleeding. I don't know why they use different values than the +original paper. + + +Interpretation: + +This benchmark is intended to model a real world server workload. +But the use of a uniformly distribution of allocation sizes clearly differs from +real applications. Although the results can be a metric of scalability and +false sharing because it uses multiple threads, which pass memory around. +""" import re @@ -25,12 +54,7 @@ THROUGHPUT_RE = re.compile("^Throughput =\\s*(?P<throughput>\\d+) operations per class BenchmarkLarson(Benchmark): - """Larson server benchmark - - This benchmark is courtesy of Paul Larson at Microsoft Research. It - simulates a server: each thread allocates and deallocates objects, and then - transfers some objects (randomly selected) to other threads to be freed. - """ + """Definition of the larson benchmark""" def __init__(self): name = "larson" |