jemalloc.NET | A native memory manager for .NET | Machine Learning library
kandi X-RAY | jemalloc.NET Summary
kandi X-RAY | jemalloc.NET Summary
Get the latest 0.2.x release from the releases page. jemalloc.NET is a .NET API over the jemalloc native memory allocator and provides .NET applications with efficient data structures backed by native memory for large scale in-memory computation scenarios. jemalloc is "a general purpose malloc(3) implementation that emphasizes fragmentation avoidance and scalable concurrency support" that is widely used in the industry, particularly in applications that must scale and utilize large amounts of memory. In addition to its fragmentation and concurrency optimizations, jemalloc provides an array of developer options for debugging, monitoring and tuning allocations that makes it a great choice for use in developing memory-intensive applications.
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QUESTION
High-performance malloc implementations often implement segregated free lists, that is, each of the more common (smaller) sizes gets its own separate free list.
A first attempt at this could say, below a certain threshold, the size class is just the size divided by 8, rounded up. But actual implementations have more nuance, arranging the recognized size classes on something like an exponential curve (but gentler than simply doubling at each step), e.g. http://jemalloc.net/jemalloc.3.html
I'm trying to figure out how to convert a size to a size class on some such curve. Now, in principle this is not difficult; there are several ways to do it. But to achieve the desired goal of speeding up the common case, it really needs to be fast, preferably only a few instructions.
What's the fastest way to do this conversion?
...ANSWER
Answered 2021-Oct-30 at 04:22In the dark ages, when I used to worry about those sorts of things, I just iterated through all the possible sizes starting at the smallest one.
This actually makes a lot of sense, since allocating memory strongly implies work outside of the actual allocation -- like initializing and using that memory -- that is proportional to the allocation size. In all but the smallest allocations, that overhead will swamp whatever you spend to pick a size class.
Only the small ones really need to be fast.
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