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Round 18 results - TechEmpower Framework Benchmarks
In the following tests, we have measured the performance of several web application platforms, full-stack frameworks, and micro-frameworks (collectively, "frameworks"). For more information, read the introduction, motivation, and latest environment details.
Benchmark  web  WebPerformance 
yesterday by colin.jack
wg/wrk: Modern HTTP benchmarking tool
Modern HTTP benchmarking tool. Contribute to wg/wrk development by creating an account on GitHub.
benchmarking  tools  http  performance  benchmark  testing  load  web  github  server 
2 days ago by omen
pzolee / tcpserver / wiki / Home — Bitbucket

This program is designed for WiFi Speed Test for Android application for server side of local computers.

If you have never heard about this program, you can find more details and information in my blog:
internet  performance  wifi  networking  tool  free  python  linux  windows  benchmark  bitbucket  links  support 
8 days ago by ezequiel
Understand Linux Load Averages and Monitor Performance of Linux
In this article, we will explain one of the critical Linux system administration tasks – performance monitoring in regards to system/CPU load and load averages.
performance  tool  tools  linux  kernel  benchmark  tips  info  example  cli  software  tutorial  cpu  2017  article 
9 days ago by ezequiel
zeebo/blake3: Pure Go implementation of BLAKE3 with AVX2 and SSE4.1 acceleration
Pure Go implementation of BLAKE3 with AVX2 and SSE4.1 acceleration - zeebo/blake3
golang  rust  benchmark  hashing 
11 days ago by geetarista
Memory Bandwidth Napkin Math
Reading random values RAM is slow, 0.46 GB/s. Reading random values from L1 cache is very very fast, 13 GB/s. This is faster than the 11 GB/s performance we got sequentially reading int32 from RAM.
Random access from RAM is slow. Catastrophically slow. Less than 1 GB/s slow for both int32. Random access from the cache is remarkably quick. It's comparable to sequential RAM performance.

Single Threaded Comparison
Let this sink in. Random access into the cache has comparable performance to sequential access from RAM. The drop off from sub-L1 16 KB to L2-sized 256 KB is 2x or less.

I think this has profound implications.

Linked Lists Considered Harmful

Pointer chasing is bad. Really, really bad. Just how bad is it? I made an extra test that wraps matrix4x4 in std::unique_ptr. Each access has to go through a pointer. Here's the terrible, horrible, no good, very bad result.

1 Thread | matrix4x4 | unique_ptr | diff |
Large Block - Seq | 14.8 GB/s | 0.8 GB/s | 19x |
16 KB - Seq | 31.6 GB/s | 2.2 GB/s | 14x |
256 KB - Seq | 22.2 GB/s | 1.9 GB/s | 12x |
Large Block - Rand | 2.2 GB/s | 0.1 GB/s | 22x |
16 KB - Rand | 23.2 GB/s | 1.7 GB/s | 14x |
256 KB - Rand | 15.2 GB/s | 0.8 GB/s | 19x |

6 Threads | matrix4x4 | unique_ptr | diff |
Large Block - Seq | 34.4 GB/s | 2.5 GB/s | 14x |
16 KB - Seq | 154.8 GB/s | 8.0 GB/s | 19x |
256 KB - Seq | 111.6 GB/s | 5.7 GB/s | 20x |
Large Block - Rand | 7.1 GB/s | 0.4 GB/s | 18x |
16 KB - Rand | 95.0 GB/s | 7.8 GB/s | 12x |
256 KB - Rand | 58.3 GB/s | 1.6 GB/s | 36x |
Sequentially summing values behind a pointer runs at less than 1 GB/s. Random access, which misses the cache twice, runs at just 0.1 GB/s.

Pointer chasing is 10 to 20 times slower. Friends don't let friends used linked lists. Please, think of the children cache.
hardware  intel  memory  benchmark  performance  test  cpu 
11 days ago by some_hren
GNU Compiler Collection Flags
Commands and Options Used to Submit Benchmark Runs

SPECrate runs might use one of these methods to bind processes to specific processors, depending on the config file.

Linux systems: the numactl command is commonly used. Here is a brief guide to understanding the specific command which will be found in the config file:

syntax: numactl [--interleave=nodes] [--preferred=node] [--physcpubind=cpus] [--cpunodebind=nodes] [--membind=nodes] [--localalloc] command args ...
numactl runs processes with a specific NUMA scheduling or memory placement policy. The policy is set for a command and inherited by all of its children.
--localalloc instructs numactl to keep a process memory on the local node while -m specifies which node(s) to place a process memory.
--physcpubind specifies which core(s) to bind the process. In this case, copy 0 is bound to processor 0 etc.
For full details on using numactl, please refer to your Linux documentation, man numactl
compiler  c  c++  profiling  Benchmark  numactl  cpu-affinity 
12 days ago by negril
Speed test - how fast is your internet? | DSLReports, ISP Information
Test your download, upload and latency from a mobile phone up to optical fiber, and everything between. This test is pure HTML5

This test requires your browser's full attention for accurate results. Run the test when your network is quiet, and don't switch to other applications or change browser tabs during the test. A few Windows security and privacy software packages can block the test or slow the browser.
test  internet  wifi  networking  webapp  html5  performance  benchmark 
13 days ago by ezequiel

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