Use xxHash instead of SHA-256 on incoming transaction hashes cache

[viossat]

Description

Use xxHash instead of SHA-256 on incoming transaction hashes cache to reduce CPU load and allows higher TPS throughput.

Fixes #1171

Type of change

• Enhancement (a non-breaking change which adds functionality)

Checklist:

• My code follows the style guidelines for this project
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes

[muXxer]

Nice one! :)

[GalRogozinski]

We need to do some tests to see how this improves the cpu load

If @viossat or @muXxer did their own tests I will be happy if they upload the results here

[muXxer]

I only made some benchmarks in golang, sorry. But here are my results for golang:

Running tool: /usr/local/go/bin/go test -benchmem -run=^$ -bench . -coverprofile=/tmp/vscode-gohKcwB0/go-code-cover

goos: linux
goarch: amd64
BenchmarkMD5-4               10000000           154 ns/op           0 B/op           0 allocs/op
BenchmarkSHA256-4            10000000           229 ns/op           0 B/op           0 allocs/op
BenchmarkHighwayHash-4       30000000          41.3 ns/op           0 B/op           0 allocs/op
BenchmarkXXHash-4           100000000          10.4 ns/op           0 B/op           0 allocs/op
PASS

229ns vs 10.4ns on my machine

This is called more often than Curl, depending on the amount of neighbors you have.
During a spam event, this should be much worse than at current network rate.
Also when a node is syncing and requesting a lot of tx from the neighbors, this should affect the CPU load.

[GalRogozinski]

After 1.6.1 will be out we will check if this should be merged

[viossat]

Here a quick benchmark between SHA-256 and two xxHash libs (LZ4 and Zero-Allocation-Hashing) hashing the same million of 1653-byte arrays. The PR implements the last one. Please note the net.jpountz.xxhash lib seems the fastest below 1 million.

hash function	time (ms)
java.security.MessageDigest ("SHA-256")	7204
net.jpountz.xxhash.XXHash32	260
net.jpountz.xxhash.XXHash64	180
net.openhft.hashing.LongHashFunction	163

That means a 5-neighbors node at 100 TPS would only save about 1 second every 5 minutes.

[muXxer]

At higher rate this makes more impact

>>> (7.204/1000000.0)*5000*60*5
10.806000000000001
>>> (0.163/1000000.0)*5000*60*5
0.24450000000000002

Thats already a difference of 10.56s every 5 Minutes with 1000 TPS and 5 neighbors (28.4 % CPU load).
:wen: 1000 TPS eoy? :)

[alon-e]

looks good!

[GalRogozinski]

I want to finish #1328 first so that we can track the overall improvement

[karimodm]

gg