The LRU lock and mmap_sem [LWN.net]
Did you know...?LWN.net is a subscriber-supported publication; we rely on subscribers to keep the entire operation going. Please help out by buying a subscription and keeping LWN on the net. The kernel's memory-management subsystem has to manage a great deal of concurrency; that leads to an ongoing series of locking challenges that sometimes seem intractable. Two recurring locking issues — the LRU
GitHub - lasp-lang/partisan: High-performance, high-scalability distributed computing for the BEAM.
Partisan is a scalable and flexible, TCP-based membership system and distribution layer for the BEAM. It bypasses the use of Distributed Erlang for manual connection management via TCP, and has several pluggable backends for different deployment scenarios. Partisan is a runtime system that enables greater scalability and reduced latency for distributed actor applications. Partisan improves scalabi
Spinlocks and Read-Write Locks
Spinlocks and Read-Write Locks Most parallel programming in some way will involve the use of locking at the lowest levels. Locks are primitives that provide mutual exclusion that allow data structures to remain in consistent states. Without locking, multiple threads of execution may simultaneously modify a data structure. Without a carefully thought out (and usually complex) lock-free algorithm, t
Why does one NGINX worker take all the load?
Why does one NGINX worker take all the load?2017-10-23 Scaling up TCP servers is usually straightforward. Most deployments start by using a single process setup. When the need arises more worker processes are added. This is a scalability model for many applications, including HTTP servers like Apache, NGINX or Lighttpd. CC BY-SA 2.0 image by Paul Townsend Increasing the number of worker processes
on mutex performance and WTF::Lock | Nathan's Blog
One of the things I’ve been doing this quarter is removing Gecko’s dependence on NSPR locks. Gecko’s (non-recursive) mutexes and condition variables now use platform-specific constructs, rather than indirecting through NSPR. This change makes things smaller, especially on POSIX platforms, and uses no dynamic memory allocation, so there are fewer untested failure paths. I haven’t rigorously benc
Consistent Hashing with Bounded Loads
Designing algorithms for balanced allocation of clients to servers in dynamic settings is a challenging problem for a variety of reasons. Both servers and clients may be added and/or removed from the system periodically, and the main objectives of allocation algorithms are: the uniformity of the allocation, and the number of moves after adding or removing a server or a client. The most popular sol
Scalability! But at what COST?
Michael Isard, Derek Murray, and I recently sent in a HotOS submission (it’s not blind, so no harm talking about it, we think). The subject is hinted at from the post title (stolen from the paper title): Big data systems may scale well, but this can often be just because they introduce a lot of overhead. Rather than making your computation go faster, the systems introduce substantial overheads whi
Neil J. Gunther - Wikipedia
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Databases at 14.4Mhz
Failing at scaling When we started building FoundationDB five years ago, my co-founder and I wrote down our big hairy goals for the distributed key-value database we were dreaming up: Fast, strict ACID transactions Even during failure scenarios Even across multiple keys on different nodes Read latencies below 500 microseconds Commit (write) latencies below 2 milliseconds Scalability to 100,000,000
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3. 3 低レイテンシーã®é‡è¦æ€§ • Amazon 社 • 1秒ã®é…延㧠7% ãŒé›¢è„±ã€11% ã® page views ãŒå¤±ã‚れる • 100ms ã®é…延減少㧠1% 売り上ã’増大ã€Amazon ã§ã¯åˆè¨ˆã§å¹´ $480M å¢—åŠ â€¢ Microsoft 社 • 2秒ã®é…延ã§ãƒ¦ãƒ¼ã‚¶å½“ãŸã‚Šã®å£²ã‚Šä¸Šã’ -4.3% • Google 社 • 検索çµæžœãƒšãƒ¼ã‚¸ã‚’10ã‹ã‚‰30é …ç›®ã«ã™ã‚‹ã¨ã€ãƒãƒ¼ãƒ‰æ™‚間㌠400ms ã‹ã‚‰ 900ms ã¨ãªã‚Šã€25% ãŒé›¢è„± 4. 4 Web ã®ã‚¹ã‚±ãƒ¼ãƒ«ã‚¢ã‚¦ãƒˆã§ã®è€éšœå®³æ€§ • セッション状態ã®è¤‡è£½ã®èª² 題： 一貫性ã®ä¿è¨¼ • NoSQLã€RDB ã«æ°¸ç¶šåŒ–？ • ãã®ä»–ã®èª²é¡Œï¼š • グループメンãƒãƒ¼ã®éšœå®³ç›£è¦– • 状態ã®æŽ’他制御 • Master/slave ã§ã® master ã®éšœå®³ã€ãƒ•ã‚§ã‚¤ãƒ«ã‚ªãƒ¼ãƒãƒ¼ Web Servers Database Servers Memcach
The Secret to 10 Million Concurrent Connections -The Kernel is the Problem, Not the Solution - High Scalability -
Now that we have the C10K concurrent connection problem licked, how do we level up and support 10 million concurrent connections? Impossible you say. Nope, systems right now are delivering 10 million concurrent connections using techniques that are as radical as they may be unfamiliar. To learn how it’s done we turn to Robert Graham, CEO of Errata Security, and his absolutely fantastic talk at Shm
The Tail at Scale – Communications of the ACM
Software techniques that tolerate latency variability are vital to building responsive large-scale Web services. Systems that respond to user actions quickly (within 100ms) feel more fluid and natural to users than those that take longer.3 Improvements in Internet connectivity and the rise of warehouse-scale computing systems2 have enabled Web services that provide fluid responsiveness while consu
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Applied Performance Theory
Some more details on Read-Log-Update [LWN.net]
Userspace RCU
ffwd: delegation is (much) faster than you think | the morning paper
Queueing Theory
Gmane -- Mail To News And Back Again
Service Architectures at Scale: Lessons from Google and eBay
InfiniSQL
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