We have used memtier_benchmark (developed by Redis Labs) as a load generator for benchmarking Memcached. Each test was configured to run with multiple threads, multiple clients per thread, and with pipelining enabled.

We recommend compiling Memcached server with GCC 10.2 or newer as newer compilers have made significant progress towards generating optimized code that can improve performance.

We used CentOS 8.4 (kernel 4.18) with Memcached 1.6.9 compiled with GCC 10.2 for our tests. We compared Ampere Altra Max M128-30, AMD EPYC 7763 and Intel Ice Lake Refresh (refer to the chart below for results). For each of the tests, we used similar clients to generate requests to Memcached-server.

Since it is realistic to measure throughput under a specified Service Level Agreement (SLA), we have used a 99th percentile latency (p.99) of 1 millisecond. This ensures that 99 percent of the requests have a response time of 1 ms in the worst case.

The test ran for 2 minutes with a 1:10 set:get ratio (1 key/value write and 10 key/value read) and 128 bytes payload, which is common for in-memory caches. We initially used an appropriate number of clients and threads/client to load one instance of Memcached server, while ensuring the p.99 latency was at most 1 ms. Pipelining feature in Memcached allows client to pack multiple requests into one single request packet which can reduce packet processing overhead. This feature can dramatically reduce response times and we used 126 concurrent pipelined requests for Ampere Altra Max M128- 30.

Next, we successively increased the number of Memcached instances till one or more instances violated the p.99 latency SLA. The aggregate throughput of all instances was used as the primary performance metric. We ran the test three times and saw minimal run-to-run variations.

As can be seen in the chart above, we observed up to a 1.74x on Ampere Altra Max compared to Intel 8380 (see chart).

We observed up to a 1.23x improvement in performance on Ampere Altra Max compared to AMD 7763 (see chart).

For large-scale cloud deployments, performance/watt (i.e. energy efficiency) is an important metric in addition to raw performance. Ampere Altra Max processors have 2.66x better performance/watt under a specified SLA than that on Intel servers and 1.87x higher performance/watt compared to that on AMD servers.

Fast in-memory caches are used in most cloud usages today. Memcached is a popular high throughput in-memory key-value store that is applicable to low latency applications in a scale out configuration. Ampere Altra Max is designed to deliver exceptional performance and energy efficiency for cloud native applications like Memcached. In Ampere’s testing, the processor demonstrated up to 1.74x performance improvements and they achieved up to 2.66x energy efficiency improvements. For more information on this workload or other workloads our engineers have been working on, please visit https://solutions.amperecomputing.com/.

All data and information contained herein is for informational purposes only and Ampere reserves the right to change it without notice. This document may contain technical inaccuracies, omissions and typographical errors, and Ampere is under no obligation to update or correct this information. Ampere makes no representations or warranties of any kind, including but not limited to express or implied guarantees of noninfringement, merchantability, or fitness for a particular purpose, and assumes no liability of any kind. All information is provided “AS IS.” This document is not an offer or a binding commitment by Ampere. Use of the products contemplated herein requires the subsequent negotiation and execution of a definitive agreement or is subject to Ampere’s Terms and Conditions for the Sale of Goods.

System configurations, components, software versions, and testing environments that differ from those used in Ampere’s tests may result in different measurements than those obtained by Ampere.

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