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Systems software research was dying 21 years ago when Rob gave that talk. (A better URL for the slides is http://doc.cat-v.org/bell_labs/utah2000/utah2000.html; the version you linked is pretty incomplete.) Since then systems software research has been quite vital, in significant part due to Rob himself; in no particular order, relevant developments in systems software research since Rob's paper include Golang, MapReduce, HTML5 (including Web Workers, <canvas>, and WebSockets), Sawzall, Hadoop, Rust, wasm, Fuchsia (as you point out), V8, protobufs, Thrift, Docker, Xen, AWS, Azure, ZFS, btrfs, BitTorrent, Kafka, nearly all of Google's "warehouse-scale computing" stuff, memcached, OpenID, QEMU†, kvm, PyPy, SPARK, Julia and almost all the automatic differentiation stuff, Clojure, iOS, Swift, Factor, AMQP, RabbitMQ, ZeroMQ, Jupyter, the mainstream use of AJAX and Comet, QUIC and HTTP/2, Valgrind, LLVM, Kotlin, Bitcoin, Ethereum, OTR and Signal, Android, Dalvik, reproducible builds, seL4, Zig, Pony, CapnProto, Sandstorm.io, Fastly's fast-purging CDN, the Varnish cache it's based on, the fast SSDs that enabled it, TileDB as you mention (and Parquet), time-series databases like InfluxDB in general, Python 3, Racket, major new developments in ECMAScript, JSON, Z3, entity-component systems, general-purpose GPU computing, Intel ME (for better or worse, mostly worse, it's certainly relevant systems software research), OTR and Signal, Tor, Chrome, Firefox, Node.js, npm, LevelDB, record-replay for time-travel debugging, UBsan and Asan, stack canaries, epoll, io_uring, Qubes, Vulkan, CUDA, Wayland, Haskell's STM, XMPP, DTrace, the whole megillah around the shift to manycore, WPA for Wi-Fi, most of the work in making secure protocols resistant to timing and compression attacks, Git, SyncThing, ownCloud, rsync, zsync, GFS, BigTable, Cassandra, MQTT, and on and on and on. Oh yeah, and also eBPF. Putting your filesystem on a ramdisk is a good idea but it's hardly innovative. ______ † https://web.archive.org/web/20030601085257/http://fabrice.be... |
I am way late to the party, but here goes: In 2007 I started working for a company in Norway that had developed their own database, from hardware and up. It included parallell processing (a few thousand processors when I joined) and everything hosted in memory. It was fast. Boot up took a while though, since it had to load everything from disks to memory.
When I joined they were on the third iteration already, the first version went live back in 1992.
We have since retired the concept since off-the-shelf hardware caught up in terms of speed and lower cost, also it didn't scale very well.