.. Copyright (c) <2010-2017>, Intel Corporation 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 Intel Corporation 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 THE COPYRIGHT OWNER 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. ================================================== Sample Application Tests: Elastic Flow Distributor ================================================== Description ----------- EFD is a distributor library that uses perfect hashing to determine a target/value for a given incoming flow key. It has the following advantages: 1. It uses perfect hashing it does not store the key itself and hence lookup performance is not dependent on the key size. 2. Target/value can be any arbitrary value hence the system designer and/or operator can better optimize service rates and inter-cluster network traffic locating. 3. Since the storage requirement is much smaller than a hash-based flow table (i.e. better fit for CPU cache), EFD can scale to millions of flow keys. 4. With the current optimized library implementation, performance is fully scalable with any number of CPU cores. For more details, please reference to dpdk online programming guide. Prerequisites ============= Two ports connect to packet generator. DUT board must be two sockets system and each cpu have more than 16 lcores. Test Case: EFD function unit test --------------------------------- Start test application and run efd unit test:: test> efd_autotest Verify every function passed in unit test Test Case: EFD performance unit test ------------------------------------ Start test application and run EFD performance unit test:: test> efd_perf_autotest Verify lookup and lookup bulk cpu cycles are reasonable. Verify when key size increased, no significant increment in cpu cycles. Verify when value bits increased, no significant increment in cpu cycles. Compare with cuckoo hash performance result, lookup cycles should be less. Test Case: Load balancer performance based on EFD ------------------------------------------------- In EFD sample, EFD work as a flow-level load balancer. Flows are received at a front end server before being forwarded to the target back end server for processing. This case will measure the performance of flow distribution with different parameters. Value bits: number of bits of value that be stored in EFD table Nodes: number of back end nodes Entries: number of flows to be added in EFD table +--------------+-------+-----------+------------+ | Value Bits | Nodes | Entries | Throughput | +--------------+-------+-----------+------------+ | 8 | 2 | 2M | | +--------------+-------+-----------+------------+ | 16 | 2 | 2M | | +--------------+-------+-----------+------------+ | 24 | 2 | 2M | | +--------------+-------+-----------+------------+ | 32 | 2 | 2M | | +--------------+-------+-----------+------------+ +--------------+-------+-----------+------------+ | Value Bits | Nodes | Entries | Throughput | +--------------+-------+-----------+------------+ | 8 | 1 | 2M | | +--------------+-------+-----------+------------+ | 8 | 2 | 2M | | +--------------+-------+-----------+------------+ | 8 | 3 | 2M | | +--------------+-------+-----------+------------+ | 8 | 4 | 2M | | +--------------+-------+-----------+------------+ | 8 | 5 | 2M | | +--------------+-------+-----------+------------+ | 8 | 6 | 2M | | +--------------+-------+-----------+------------+ | 8 | 7 | 2M | | +--------------+-------+-----------+------------+ | 8 | 8 | 2M | | +--------------+-------+-----------+------------+ +--------------+-------+-----------+------------+ | Value Bits | Nodes | Entries | Throughput | +--------------+-------+-----------+------------+ | 8 | 2 | 1M | | +--------------+-------+-----------+------------+ | 8 | 2 | 2M | | +--------------+-------+-----------+------------+ | 8 | 2 | 4M | | +--------------+-------+-----------+------------+ | 8 | 2 | 8M | | +--------------+-------+-----------+------------+ | 8 | 2 | 16M | | +--------------+-------+-----------+------------+ | 8 | 2 | 32M | | +--------------+-------+-----------+------------+