070316d01d
One of the ways to increase the insertion/deletion rate is to use multi-threaded insertion/deletion. Thus it's needed to have support for testing and measure those rates using flow-perf application. Now we generate cores and distribute all flows to those cores, and start inserting/deleting in parallel. The app now receive the cores count to use from command line option, then it distribute the rte_flow rules evenly between the cores, and start inserting/deleting. Each worker will report it's own results, and in the end the MAIN worker will report the total results for all cores. The total results are calculated using RULES_COUNT divided over max time used between all cores. Also this touches the memory area, since inserting using multiple cores in same time the pre solution for memory is not valid, thus now we save memory before and after each allocation for all cores. In the end we pick the min pre memory and the max post memory from all cores. The difference between those values represent the total memory consumed by the total rte_flow rules from all cores, and then report the total size of single rte_flow in byte for each port. How to use this feature: --cores=N Where 1 =< N <= RTE_MAX_LCORE Signed-off-by: Wisam Jaddo <wisamm@nvidia.com> Reviewed-by: Alexander Kozyrev <akozyrev@nvidia.com> Reviewed-by: Suanming Mou <suanmingm@nvidia.com>
19 lines
407 B
C
19 lines
407 B
C
/* SPDX-License-Identifier: BSD-3-Clause
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* Copyright 2020 Mellanox Technologies, Ltd
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*
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* This file contains the items related methods
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*/
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#ifndef FLOW_PERF_ITEMS_GEN
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#define FLOW_PERF_ITEMS_GEN
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#include <stdint.h>
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#include <rte_flow.h>
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#include "config.h"
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void fill_items(struct rte_flow_item *items, uint64_t *flow_items,
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uint32_t outer_ip_src, uint8_t core_idx);
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#endif /* FLOW_PERF_ITEMS_GEN */
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