Working on a TUI tool which demonstrates the behaviour of X86 SIMD instructions. This is all done in Go assembly, and is probably most valuable for Go programmers.
The problem for me was trying to read and understand the implementation of a swiss map implementation. The SIMD instructions were challenging to understand and the documentation felt difficult to read. I thought that if I had an interactive tool where I could set the inputs to a SIMD instruction and then read the outputs, understanding the instructions would be much easier.
This turned out to be true.
Building this tool for all AVX/AVX2 instructions turned out to be a larger task than I had expected. Naively I just went off a Wikipedia page on AXV and assumed it had listed all the instructions (this was a bad assumption).
I am nearly there. Looking forward to completing this project so I can actually use it to do some fun stuff processing text and maybe even get back to that swiss map implementation.
Location: New Zealand, Manawatu Remote: Yes Willing to relocate: No Technologies: Go, Java, Git, Erlang, Postgres, Linux Resume: https://www.linkedin.com/in/francis-stephens/ Email: francisstephens@gmail.com I work primarily on backend systems, with a strong focus on performance and system stability/resilience. I worked as a performance engineer at the mobile add-attribution company Adjust. Some interesting open-source projects include
https://github.com/fmstephe/memorymanager An exploratory manual memory allocator for building large in-memory data structures with near zero GC cost.
https://github.com/fmstephe/matching_engine A financial trading matching engine with a somewhat novel red+black tree implementation.
https://github.com/fmstephe/flib A set of packages primarily in support of a lock-free single-producer single-consumer queue.
My ideal position would be working on backend systems primarily in Go.
Location: New Zealand, Manawatu
Remote: Yes
Willing to relocate: No
Technologies: Go, Java, Git, Erlang, Postgres, Linux
Resume: https://www.linkedin.com/in/francis-stephens/
Email: francisstephens@gmail.com
I work primarily on backend systems, with a strong focus on performance and system stability/resilience. I worked as a performance engineer at the mobile add-attribution company Adjust.
Some interesting open-source projects include
Location: New Zealand, Manawatu
Remote: Yes
Willing to relocate: No
Technologies: Go, Java, Git, Erlang, Postgres, Linux
Resume: https://www.linkedin.com/in/francis-stephens/
Email: francisstephens@gmail.com
I work primarily on backend systems, with a strong focus on performance and system stability/resilience. I worked as a performance engineer at the mobile add-attribution company Adjust.
In New Zealand, where I live, the Salvation Army (charity second hand shop) offers a service where they will come and clear out a house for you. They will take everything and dispose of the trash and keep and resell anything of value.
This is really used to clear out houses of deceased relatives etc.
This doesn't resolve your problem of generally selling your used goods conveniently. But I always found it to be a really interesting service. Because it identifies that there is real practical difficulty in simply giving away a lot of goods, and the solution is to provide this complete service to make it easier.
In contrast to the popular arena based allocators (which target quickly allocating/freeing short lived per-request allocations), I am targeting an allocator for build very large in-memory dbs or caches with almost no garbage collection cost.
There's a little no-gc string interner package in there as well.
https://github.com/fmstephe/gossert
A library for adding runtime assertions to Go code. It's developed so that when the assertions are switched off the compiler should be able to completely eliminate the assertions. But this requires build tags to switch the assertions on.
If you enjoyed this, or if you need more control over some memory allocations in Go, please have a look at this package I wrote. I would love to have some feedback or have someone else use it.
It bypasses the GC altogether by allocating its own memory separately from the runtime. It also disallows pointer types in allocations, but replaces them with a Reference[T] type, which offers the same functionality. Freeing memory is manual though - so you can't rely on anything being garbage collected.
These custom allocators in Go tend to be arena's intended to support groups of allocations which live and die together. But the offheap package was intended to build large long-lived datastructures with zero garbage collection cost. Things like large in-memory caches or databases.
For the problems that arena allocators solve, relatively short lived allocations which die soon, yes. A generational collector would allow for faster allocation rates (a thread local bump allocator would become easy to use).
But very long lived data structures, like caches and in memory databases still need to be marked during full heap garbage collection cycles. These are less frequent with a generational collector though.
Location: New Zealand, Manawatu
Remote: Yes
Willing to relocate: No
Technologies: Go, Java, Git, Erlang, Postgres, Linux
Resume: https://www.linkedin.com/in/francis-stephens/
Email: francisstephens@gmail.com
I work primarily on backend systems, with a strong focus on performance and system stability/resilience. I worked as a performance engineer at the mobile add-attribution company Adjust.
Just an anecdote from work to back this up. I wrote a system that was taking requests, making another request to a service (that basically wrapped elasticsearch) and then processed the results and returned to the results to the caller.
By default the elastic-search results were paginated and defaulted to some small number in the order of 25..100. I increased this steadily upwards beyond 100,000 to the point where every request always returned the entire result in the first page. And it _transformed_ the performance of the service. From one that was unbearably slow for human users to one that _felt_ instantaneous. I had real perf numbers at the time, but now all I have are the impressions.
But the lesson on the impact of the overhead of those paginated calls was important. Obviously everything is specific and YMMV, but this something worth having in the back of your mind.
Location: New Zealand, Manawatu
Remote: Yes
Willing to relocate: No
Technologies: Go, Java, Git, Erlang, Postgres, Linux
Resume: https://www.linkedin.com/in/francis-stephens/
Email: francisstephens@gmail.com
I work primarily on backend systems, with a strong focus on performance and system stability/resilience. I worked as a performance engineer at the mobile add-attribution company Adjust.
The problem for me was trying to read and understand the implementation of a swiss map implementation. The SIMD instructions were challenging to understand and the documentation felt difficult to read. I thought that if I had an interactive tool where I could set the inputs to a SIMD instruction and then read the outputs, understanding the instructions would be much easier.
This turned out to be true.
Building this tool for all AVX/AVX2 instructions turned out to be a larger task than I had expected. Naively I just went off a Wikipedia page on AXV and assumed it had listed all the instructions (this was a bad assumption).
I am nearly there. Looking forward to completing this project so I can actually use it to do some fun stuff processing text and maybe even get back to that swiss map implementation.
https://github.com/fmstephe/simd_explorer
(This is also my first attempt at a TUI app)