I looked a bit into this a few years back and found it quite interesting. Despite them calling them "Tiny Pointers" I would say it's closer to a open addressing hash map. You have a specific key, and then you can "allocate" an entry in the hash map. This gives you back a "pointer". You can then later use the original key and the pointer together to determine the index of the entry. There's also a slight chance that the allocation will fail (similar to a hash collision in a hash map). The "trick" here is that two different keys can end up having the exact same pointer (because we're always dereferencing with the key). This makes them more compact.
I was struggling a bit to come up with good use cases for it. Their examples are all around combining them with existing data structures and they show that the space complexity is smaller, but it wasn't completely clear to me how feasible this would actually be in practice.
I read the paper a few years ago and I agree that for such an incredible algorithmic improvement, it’s not trivial to find a use case, as you still need to maintain a separate (albeit algorithmically insignificant) lookup table. When I read the paper I (mistakenly) hoped it could be used for indexing on-disk structures without ever hitting the disk for things like B tree internal nodes. To get its sweet sweet algorithmic complexity, up its sleeve is once again (as I recall) the age old trick of rebuilding the structure when the size doubles, which makes it much less efficient than it sounds for most practical use cases. I suppose one good use case for this might be compressing database indexes, where you need to maintain a separate structure anyway and the space savings can be worth it.
It isn't hard to make a datastructure that indexes into itself. BDDs, for example, are often coded in this way. I did an admittedly poor job of one at https://taeric.github.io/trading-with-bdds.html, but I think it is enough to see the idea well enough.
Didn't Python's compact dictionary implementation do this a decade ago?
"The dict type now uses a “compact” representation based on a proposal by Raymond Hettinger which was first implemented by PyPy. The memory usage of the new dict() is between 20% and 25% smaller compared to Python 3.5." -- https://docs.python.org/3.6/whatsnew/3.6.html#whatsnew36-com...
@staticmethod
def _make_index(n):
'New sequence of indices using the smallest possible datatype'
if n <= 2**7: return array.array('b', [FREE]) * n # signed char
if n <= 2**15: return array.array('h', [FREE]) * n # signed short
if n <= 2**31: return array.array('l', [FREE]) * n # signed long
return [FREE] * n
dk_indices is actual hashtable. It holds index in entries, or DKIX_EMPTY(-1)
or DKIX_DUMMY(-2).
Size of indices is dk_size. Type of each index in indices varies with dk_size:
* int8 for dk_size <= 128
* int16 for 256 <= dk_size <= 2**15
* int32 for 2**16 <= dk_size <= 2**31
* int64 for 2**32 <= dk_size
The "compact dictionary" representation you're talking about not always using 64-bit numbers, but rather using log(n)-bit values when you have n entries (i.e. using 8-bit values when there's only <= 128 entries). The paper linked here talks about pointers which uses less than log(n)-bits for n entries.
> How large do the pointers need to be? The natural answer is that each pointer uses log nbits. However, the fact that each pointer has a distinct owner makes it possible to compress the pointers to o(log n) bits.
What if you have to debug the whole situation, such that you don't always know who is the owner of a pointer you are looking at?
> A user k can call Allocate(k) in order to get a tiny pointer p; they can dereference the tiny
pointer pby computing a function Dereference(k,p) whose value depends only on k, p, and random bits;
and they can free a tiny pointer p by calling a function Free(k,p).
That is tantamount ot saying that the pointer is not actually p but the tuple <k, p>, and so its size consists of the number of bits in k, the number of bits in p plus an indication of where the division between these bits lie: where k ends and p begins.
We can abbreviate <k, p> to p in contexts where k can be implicitly understood.
Here's a somewhat related post where I argue that logic that _can_ have small pointers has lower entropy and is more optimal as bayesian model of the domain: https://benoitessiambre.com/entropy.html
I could be wrong, but I think the easiest way to think of this is to consider how much extra memory programs took when compiled with 64 bit pointers over 32 bit ones. Suddenly every pointer takes double the memory. Which, sure, isn't a huge deal if you don't have a lot of memory allocations. But, if you do, it can add up.
Places it would likely impact more than you'd realize is in higher level language arrays where each item in the array is a pointer. For similar reasons, many datastructures can be coded such that each "pointer" is an array index instead.
So, extending all of that, what if you could make your pointers even smaller than 32 bits? If you know the addressable need for where the pointer is used, there is no reason you can't go smaller.
judofyr|1 year ago
I was struggling a bit to come up with good use cases for it. Their examples are all around combining them with existing data structures and they show that the space complexity is smaller, but it wasn't completely clear to me how feasible this would actually be in practice.
qazxcvbnm|1 year ago
Izikiel43|1 year ago
https://www.quantamagazine.org/undergraduate-upends-a-40-yea...
taeric|1 year ago
CyberDildonics|1 year ago
mont_tag|1 year ago
"The dict type now uses a “compact” representation based on a proposal by Raymond Hettinger which was first implemented by PyPy. The memory usage of the new dict() is between 20% and 25% smaller compared to Python 3.5." -- https://docs.python.org/3.6/whatsnew/3.6.html#whatsnew36-com...
"Note, the sizeof(index) can be as small as a single byte for small dicts, two bytes for bigger dicts and up to sizeof(Py_ssize_t) for huge dict." -- https://mail.python.org/pipermail/python-dev/2012-December/1...
The "tiny pointers" are in the _make_index method in the proof of concept code. -- https://code.activestate.com/recipes/578375-proof-of-concept...
The logic is still present today in CPython. -- https://raw.githubusercontent.com/python/cpython/3e222e3a159...judofyr|1 year ago
yorwba|1 year ago
kragen|1 year ago
kragen|1 year ago
vlovich123|1 year ago
kazinator|1 year ago
What if you have to debug the whole situation, such that you don't always know who is the owner of a pointer you are looking at?
> A user k can call Allocate(k) in order to get a tiny pointer p; they can dereference the tiny pointer pby computing a function Dereference(k,p) whose value depends only on k, p, and random bits; and they can free a tiny pointer p by calling a function Free(k,p).
That is tantamount ot saying that the pointer is not actually p but the tuple <k, p>, and so its size consists of the number of bits in k, the number of bits in p plus an indication of where the division between these bits lie: where k ends and p begins.
We can abbreviate <k, p> to p in contexts where k can be implicitly understood.
BenoitEssiambre|1 year ago
levzettelin|1 year ago
taeric|1 year ago
Places it would likely impact more than you'd realize is in higher level language arrays where each item in the array is a pointer. For similar reasons, many datastructures can be coded such that each "pointer" is an array index instead.
So, extending all of that, what if you could make your pointers even smaller than 32 bits? If you know the addressable need for where the pointer is used, there is no reason you can't go smaller.
trymas|1 year ago
ceeam|1 year ago
kittikitti|1 year ago
wbolt|1 year ago
unknown|1 year ago
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