Testing performance

[tevador]

I have pushed a test release of the C++ generator.

You can build it yourself (instructions here) or download precompiled binaries from here. The precompiled binaries require AVX instruction set, so if your CPU doesn't support it, you have to build your own.

It consists of two binaries: randomjs (the generator) and xst (javascript engine).

It generates and executes 1000 programs and calculates Blake2b hashes of all outputs.

Post your performance numbers and CPU specs.

Xeon E3-1245 @3.7 GHz (Debian 9)

> ./randomjs
Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 100.232 programs per second

Xeon (Skylake, IBRS) @ 2.1 GHz (Ubuntu 18.04 LTS)
Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79 Performance: 62.0579 programs per second

[SChernykh]

Intel Core i7-7820X @ 3.6 GHz (Windows 10). Built all binaries (release build) myself.

Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 129.94 programs per second

[JohannesLau]

From precompiled binaries.
Ryzen 1700x @ 3.4GHz Windows 10
Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79 Performance: 86.3199 programs per second

[SChernykh]

Intel Core i7-7820X @ 3.6 GHz (Windows 10). Rebuilt all binaries using profile guided optimizations: 6.4% faster.

Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 138.256 programs per second

Edit: here are the precompiled binaries on the same PC

Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 130.962 programs per second

[tevador]

Raspberry Pi 3 @ 1.2 GHz

Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 13.9537 programs per second

(Note: To build for ARM, the currently used SSE2 version of Blake2b must be replaced by the reference or NEON optimized version.)

[Cactii1]

Core i7-4700HQ @ 2.4 GHz Windows 8.1 with 16gigs RAM

..\Wownero-Test>randomjs.exe
Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 96.2629 programs per second

..\Wownero-Test>randomjs.exe
Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 95.4948 programs per second

..\Wownero-Test>randomjs.exe
Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 96.447 programs per second

..\Wownero-Test>randomjs.exe
Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 94.1722 programs per second

..\Wownero-Test>randomjs.exe
Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 99.5576 programs per second

[SChernykh]

@tevador Your precompiled binaries crash with exception code 0xC000001D (illegal instruction) on Pentium G5400 (Coffee Lake) because it doesn't support AVX. I had to recompile it with SSE2.

Intel Core i5-3210M @ 2.9 GHz, precompiled binaries:

Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 75.0907 programs per second

Intel Core i5-3210M @ 2.9 GHz, my binaries with PGO:

Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 84.095 programs per second

Intel Pentium G5400 @ 3.7 GHz, my binaries without PGO:

Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 109.548 programs per second

Intel Pentium G5400 @ 3.7 GHz, my binaries with PGO:

Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 116.807 programs per second

[tevador]

@SChernykh Yes, the precompiled binaries require AVX. I added a note to the original comment. I didn't realize there were still modern CPUs where Intel disables it.

Do the profile guided optimizations work in general or just for these particular 1000 programs? You can run a different set of programs by modifying the block header template in main.cpp. It would be best to read the block template and nonce count from the command line, but I didn't have time to implement it yet.

[SChernykh]

@tevador 1000 programs (~10 seconds of CPU time) is a big enough sample set for PGO to work well. It optimizes C/C++ code on low level and only needs execution statistics - which branches are executed more often, which if are taken and which are not and so on. In my experience, PGO almost always gives some improvement.

[zpalmtree]

Ryzen 1600 @ 3.6 GHz (Linux)

Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 115.622 programs per second

[SChernykh]

Raspberry Pi 3 @ 1.2 GHz

@tevador Was it 64 bit or 32 bit build? Are there any differences between 32 and 64 bit?

[tevador]

@SChernykh Ubuntu 16.04 armv7l (32bit). Haven't tested a 64bit build since the software support is still a bit lacking.

[SChernykh]

Ryzen 1700 @ 3.6 GHz, Windows 10 (original testing binaries)

Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 92.7852 programs per second

[SChernykh]

Finally found a way to test it on 64-bit ARM - there are a number of cloud hosting providers that have ARM servers.

OS: Ubuntu 18.04 LTS
Compiler: g++ (Ubuntu 8-20180414-1ubuntu2) 8.0.1 20180414 (experimental) [trunk revision 259383]
Processor: Cavium ThunderX 88XX @ 2GHz (aarch64)

Cumulative output hash: bb3bffd3d0eef49066bf5c8e664c082c502fe021a7cdc0cd0c44fe1990560b79
Performance: 17.4324 programs per second