#Ethereum wallet downloading blocks archive
#Ethereum wallet downloading blocks full

#Ethereum wallet downloading blocks archive

WeвЂ™ve run an archive sync benchmark on two m5.2xlarge AWS EC2 instances (8 core, 32 GiB RAM, 3TiB EBS SSD) with -cache=4096 -syncmode=full -gcmode=archive.

The reason for the higher disk IO is due to using less memory for caching, having to push more aggressively to disk. *Whilst the performance is similar, weвЂ™ve achieved that while reducing the memory use by about 1/3rd and completely removing spurious memory peaks (Shanghai DoS).

#Ethereum wallet downloading blocks full

WeвЂ™ve run a full sync benchmark on two i3.2xlarge AWS EC2 instances (8 core, 61 GiB RAM, 1.9 TiB NVMe SSD) with -cache=4096 -maxpeers=50 -syncmode=full. WeвЂ™ve run a fast sync benchmark on two i3.2xlarge AWS EC2 instances (8 core, 61 GiB RAM, 1.9 TiB NVMe SSD) with -cache=4096 -maxpeers=50 (defaults on v1.9.0) on the 25th of April. This work was mostly done by PГ©ter SzilГЎgyi. By temporarily allocating pruning caches to fast sync blooms, weвЂ™ve been able to short circuit most data accesses in-memory.

The discovery of a LevelDB compaction overhead during the state sync phase of fast sync.

Props for these efforts (spanning 6-9 months) go to Alexey Akhunov, Gary Rong, PГ©ter SzilГЎgyi and Matthew Halpern.

The analysis and optimization of our database schemas, trying to both remove any redundant data as well as redesign indexes for lower disk use (sometimes at the cost of a slight CPU hit).

Shoutout goes to Martin Holst Swende for pioneering this effort. This led to both fixes in Geth as well as infos funneled into the Eth 1.x scaling discussions.

The analysis and optimization of various EVM opcodes, aiming to find outliers both in GethвЂ™s EVM implementation as well as EthereumвЂ™s protocol design in general.

This resulted in stabilizing GethвЂ™s memory usage even during the import of the Shanghai DoS blocks and speeding up overall block processing by concurrent heuristic state prefetching.

The analysis and optimization of the account and storage trie access patterns across blocks.

Huge shoutout to Gary Rong for his relentless efforts, especially as his work is beneficial to the entire Go community. This caused Geth to be starved and stalled, exponentially getting worse as the database grew.

The discovery and optimization of a quadratic CPU and disk IO complexity, originating from the Go implementation of LevelDB.

Among the many improvements, the highest impact ones were:

Over the past 6 months, weвЂ™ve tried to dissect the different components that are on the critical path of block processing, in an attempt to identify and optimize some of bottlenecks. ItвЂ™s interesting to realize that the вЂњPerformanceвЂќ section was somewhere at the end of previous announcements, but over the years it became one of the most sought after improvement. Some of the features mentioned here have been silently shipped over the course of the 1.8.x release family, but weвЂ™ve deemed them important enough to explicitly highlight. We also recommend a fresh fast sync as it can drastically reduce the database size. The v1.9.0 release contains database schema changes, meaning itвЂ™s not possible to downgrade once updated. Warning: WeвЂ™ve tried our best to squash all the bugs, but as with all major releases, we advise everyone to take extra care when upgrading. After many months of silence, weвЂ™re proud to announce the v1.9.0 release of Go Ethereum! Although this release has been in the making for a lot longer than we anticipated, weвЂ™re confident there will be some juicy feature for everyone to enjoy!