4 ms·

> Example: ~10M records are processed and transformed, various computations occur, and ~100K records are spit out. Lots of statistics. One type of run takes 12

> Example: ~10M records are processed and transformed, various computations occur, and ~100K records are spit out. Lots of statistics. One type of run takes 12 hours on an 8GB, 4-core Linux box That seems insanely slow, unless they are doing something insanely complex. In other words, this doesn't tell us very much.

mcav 17y ago
12 hours / 10,000,000 records = 4.32ms/record concurrently. (4 cores maxed out ≅ 16ms per item?) Doesn't tell us much, but that doesn't seem insanely slow either, necessarily.
- barrkel 17y ago
  Assuming pretty cache-optimal code and 1.5GHz ops with no superscalar gains, that's over 25 million operations per record. Most PC video games, for example, expect a refresh rate somewhere between 30Hz and 60Hz. 60Hz gives you 17ms for an entire frame, in which it's doing an incredible amount of work: drawing a whole scene, updating the world, running physics, etc. etc. I think you have too low expectations. Modern hardware is very, very fast.
  - greendestiny 17y ago
    This whole discussion is silly, there isn't nearly enough information given in the post to infer anything. The author is just making the point that it isn't a toy application.
  - KirinDave 17y ago
    This seems to be a somewhat unfair comparison you are drawing. Video games use dedicated hardware to achieve their drawing throughput, and frequently for their sound and physics throughput. 4.32ms/rec in a high-level garbage collected language based around a data structure like the cons cell is something that is an impressive testament. As has been said, though, this is all speculation.
    - barrkel 17y ago
      If almost all allocations are specific to the processing of a record, and become garbage after that record is done with, GC is almost free. GC cost is proportional to retained allocations, not allocations made; and if old generation memory is never modified to point to new allocations, it doesn't even need to be scanned (this can be detected by write barriers, either injected into JIT code or via page faults, so it can be quite fine-grained). That's why GC is asymptotically faster than manual allocation and ideally suited to record-processing and server request/response kinds of applications. If it were using manual paired allocate/free memory management, it would actually be more impressive. And it's not 4.32ms/rec; that it's 4.32/rec with 4 cores, so estimating around 17ms (like the graphics frame) is closer. I don't agree with your suggestion that the fact that because graphics is usually accelerated and physics very rarely is, the comparison is unfair. Take a look at Pixomatic that Mike Abrash worked on. DirectX 7-level API, done entirely in software; and efficient enough that the game can still do all its work in its own time. Games still have to pump an awful lot of data through to the hardware; the hardware isn't going to do all the high-level scene graph calculations, culling and occlusion itself. The hardware expects a list of pretty basic primitives, and takes care of transforming them into the view frustum, with depth converting into Z-buffer value. The game still needs to make sure it doesn't give the hardware too much stuff that isn't actually intersecting with the view frustum.
      - KirinDave 17y ago
        We're not talking about the implementation details here, we're talking about the perception of dynamic garbage collected languages, which this summary helps to shift from an unfairly negative to a more balanced light. I'm well aware of why generational GC could be a faster choice for this kind of record processing (then again, we simply do not know from the description given how much information is shared). As for the comparison being unfair, the person who initially made that comparison was you, sir. Bringing real-time visual simulation into the equation is unfair for a variety of reasons, including the fact that a lot more research has been done in that field's optimization. I'm not sure exactly what you want from a simple high-level example that "Yes, Clojure can be used to do real work," but I don't think anyone here is going to give it to you if you set such outlandish goals as the tip of a heavily funded branch of computer science and mathematics involving real-time rendering.
  - mseebach 17y ago
    > that's over 25 million operations per record. If the algorithm is Θ(n*n) it's suddenly a bit more impressive.
dgreensp 17y ago
My "slow sense" is tingling too. I'm deadly curious to know how fast I could make that "12-hour" job using Scala or Java. I've done extensive work with Scala, Java, and bytecodes; writing performant Scala code requires some knowledge of the JVM and how Scala is compiled, and requires sacrificing some of its power; but because the static typing and method dispatching is so similar to Java's, you can get there. From everything I've read about Clojure, it sounds a whole level less efficient. Not trying to knock Clojure, but 12 hours just sounds way way too long without more explanation.
- lucifer 17y ago
  "From everything I've read about Clojure, it sounds a whole level less efficient." Curious as to what you have read regarding clojure performance. I recall hearing Cliff Click giving it a thumbs up at a JVM language summit: http://www.infoq.com/presentations/click-fast-bytecodes-funny-languages http://www.infoq.com/presentations/click-fast-bytecodes-funn... This may also be apropos: http://groups.google.com/group/clojure/msg/cccf532ca04fcdf4?dmode=source http://groups.google.com/group/clojure/msg/cccf532ca04fcdf4?...
  - dkersten 17y ago
    And I've read claims that with type annotations you can get bytecode on-par or close to that of pure Java.
- tensor 17y ago
  How can anyone even approach this with a straight face? You don't even know what they are computing! If you want to question clojure's performance for technical reasons, do that. But let's not use feelings, and instincts in discussions about concrete scientific topics. There have certainly been several interesting articles on clojure performance, and work done to improve performance for native data structures (transients). I, and no doubt many others, would be genuinely interested in performance studies on more complex concurrency problems I've seen so far.
  - lucifer 17y ago
eric_t 17y ago
I do physics simulations, and can easily reach those times with a similar amount of input. And that is with highly optimized Fortran code. But yeah, a comparison with a pure Java or C++ implementation would have been great, both in terms of speed and LOC. However, in the "real world", there usually isn't time for such silly things.
wynand 17y ago
I am crunching graph parameters based on data stored in an "input table". A single row computation can take as long as five minutes, because I compute numerous costly parameters each time. My work isn't really that complex, but it takes ages to compute everything.

mcav 17y ago

12 hours / 10,000,000 records = 4.32ms/record concurrently. (4 cores maxed out ≅ 16ms per item?) Doesn't tell us much, but that doesn't seem insanely slow either, necessarily.

barrkel 17y ago
Assuming pretty cache-optimal code and 1.5GHz ops with no superscalar gains, that's over 25 million operations per record. Most PC video games, for example, expect a refresh rate somewhere between 30Hz and 60Hz. 60Hz gives you 17ms for an entire frame, in which it's doing an incredible amount of work: drawing a whole scene, updating the world, running physics, etc. etc. I think you have too low expectations. Modern hardware is very, very fast.
- greendestiny 17y ago
  This whole discussion is silly, there isn't nearly enough information given in the post to infer anything. The author is just making the point that it isn't a toy application.
- KirinDave 17y ago
  This seems to be a somewhat unfair comparison you are drawing. Video games use dedicated hardware to achieve their drawing throughput, and frequently for their sound and physics throughput. 4.32ms/rec in a high-level garbage collected language based around a data structure like the cons cell is something that is an impressive testament. As has been said, though, this is all speculation.
  - barrkel 17y ago
    If almost all allocations are specific to the processing of a record, and become garbage after that record is done with, GC is almost free. GC cost is proportional to retained allocations, not allocations made; and if old generation memory is never modified to point to new allocations, it doesn't even need to be scanned (this can be detected by write barriers, either injected into JIT code or via page faults, so it can be quite fine-grained). That's why GC is asymptotically faster than manual allocation and ideally suited to record-processing and server request/response kinds of applications. If it were using manual paired allocate/free memory management, it would actually be more impressive. And it's not 4.32ms/rec; that it's 4.32/rec with 4 cores, so estimating around 17ms (like the graphics frame) is closer. I don't agree with your suggestion that the fact that because graphics is usually accelerated and physics very rarely is, the comparison is unfair. Take a look at Pixomatic that Mike Abrash worked on. DirectX 7-level API, done entirely in software; and efficient enough that the game can still do all its work in its own time. Games still have to pump an awful lot of data through to the hardware; the hardware isn't going to do all the high-level scene graph calculations, culling and occlusion itself. The hardware expects a list of pretty basic primitives, and takes care of transforming them into the view frustum, with depth converting into Z-buffer value. The game still needs to make sure it doesn't give the hardware too much stuff that isn't actually intersecting with the view frustum.
    - KirinDave 17y ago
      We're not talking about the implementation details here, we're talking about the perception of dynamic garbage collected languages, which this summary helps to shift from an unfairly negative to a more balanced light. I'm well aware of why generational GC could be a faster choice for this kind of record processing (then again, we simply do not know from the description given how much information is shared). As for the comparison being unfair, the person who initially made that comparison was you, sir. Bringing real-time visual simulation into the equation is unfair for a variety of reasons, including the fact that a lot more research has been done in that field's optimization. I'm not sure exactly what you want from a simple high-level example that "Yes, Clojure can be used to do real work," but I don't think anyone here is going to give it to you if you set such outlandish goals as the tip of a heavily funded branch of computer science and mathematics involving real-time rendering.
- mseebach 17y ago
  > that's over 25 million operations per record. If the algorithm is Θ(n*n) it's suddenly a bit more impressive.

dgreensp 17y ago

My "slow sense" is tingling too. I'm deadly curious to know how fast I could make that "12-hour" job using Scala or Java. I've done extensive work with Scala, Java, and bytecodes; writing performant Scala code requires some knowledge of the JVM and how Scala is compiled, and requires sacrificing some of its power; but because the static typing and method dispatching is so similar to Java's, you can get there. From everything I've read about Clojure, it sounds a whole level less efficient. Not trying to knock Clojure, but 12 hours just sounds way way too long without more explanation.

lucifer 17y ago
"From everything I've read about Clojure, it sounds a whole level less efficient." Curious as to what you have read regarding clojure performance. I recall hearing Cliff Click giving it a thumbs up at a JVM language summit: http://www.infoq.com/presentations/click-fast-bytecodes-funny-languages http://www.infoq.com/presentations/click-fast-bytecodes-funn... This may also be apropos: http://groups.google.com/group/clojure/msg/cccf532ca04fcdf4?dmode=source http://groups.google.com/group/clojure/msg/cccf532ca04fcdf4?...
- dkersten 17y ago
  And I've read claims that with type annotations you can get bytecode on-par or close to that of pure Java.
tensor 17y ago
How can anyone even approach this with a straight face? You don't even know what they are computing! If you want to question clojure's performance for technical reasons, do that. But let's not use feelings, and instincts in discussions about concrete scientific topics. There have certainly been several interesting articles on clojure performance, and work done to improve performance for native data structures (transients). I, and no doubt many others, would be genuinely interested in performance studies on more complex concurrency problems I've seen so far.
- lucifer 17y ago

eric_t 17y ago

I do physics simulations, and can easily reach those times with a similar amount of input. And that is with highly optimized Fortran code. But yeah, a comparison with a pure Java or C++ implementation would have been great, both in terms of speed and LOC. However, in the "real world", there usually isn't time for such silly things.

wynand 17y ago

I am crunching graph parameters based on data stored in an "input table". A single row computation can take as long as five minutes, because I compute numerous costly parameters each time. My work isn't really that complex, but it takes ages to compute everything.