3 ms·

It is a performance feature if you are memory constrained. Shared libraries are “shared” for a reason. On a server with high multi-tenancy the savings can be s

It is a performance feature if you are memory constrained. Shared libraries are “shared” for a reason. On a server with high multi-tenancy the savings can be significant.

jeffbee 6y ago
Not really. Dynlinking solves a memory resource problem we had in the 80s. These days the only people with the problem are the very smallest embedded systems. As for "high multi-tenancy" there's nobody out there with server occupancy as high as Google's (see the recent Borg scheduler traces for concrete data) and they statically link everything.
- binarycrusader 6y ago
  Not really. Yes, really. Dynlinking solves a memory resource problem we had in the 80s. These days the only people with the problem are the very smallest embedded systems. Definitely not true. Every bit of memory that's not available that could be shared memory instead is a reduction in memory available for filesystem caches, etc. As for "high multi-tenancy" there's nobody out there with server occupancy as high as Google's (see the recent Borg scheduler traces for concrete data) and they statically link everything. Cloud vendor computing models are not generally the computing model of the rest of the world. Comparison to their environment is not relevant to the general populace. I worked for a "big iron" OEM vendor until late 2017 and the savings were definitely still significant then both for their customers and the vendor themselves. There are numerous benefits to shared linking, that doesn't mean it's always the appropriate solution, but is not correct to claim that there are no performance benefits. Especially on more memory-constrained consumer devices, the shared memory benefits of dynamic linking are still significantly beneficial.
  - danans 6y ago
    > Cloud vendor computing models are not generally the computing model of the rest of the world. > Comparison to their environment is not relevant to the general populace. The way that Google shares server compute and memory resources is by having a service oriented architecture. A single high scale service serves many different applications, usually colocated in the same cluster or data center. Each service is based on multiple instances of a statically linked binary. At that scale, there is no point in try to use shared dynamically linked libraries to reduce consumption because you save more by either reducing increasing your own app's efficiency or relying on one of the major services rather than linking more functionality into your own app.
    - binarycrusader 6y ago
      I'm aware, which is why I specifically said that cloud vendor computing models aren't really relevant to the general populace. Google's model in particular is (or at least was) very different from other vendors.
      - jeffbee 6y ago
        I don't disagree with your point that use cases vary, but when I hear people say that "only clouds need this" I think the speaker is underestimating the size of cloud facilities. The amount of the world's computers that are in Amazon's, Google's, Facebook's, and Microsoft's clouds is a huge chunk of the total.

It is a performance feature if you are memory constrained. Shared libraries are “shared” for a reason. On a server with high multi-tenancy the savings can be significant.

jeffbee 6y ago

Not really. Dynlinking solves a memory resource problem we had in the 80s. These days the only people with the problem are the very smallest embedded systems. As for "high multi-tenancy" there's nobody out there with server occupancy as high as Google's (see the recent Borg scheduler traces for concrete data) and they statically link everything.

binarycrusader 6y ago
Not really. Yes, really. Dynlinking solves a memory resource problem we had in the 80s. These days the only people with the problem are the very smallest embedded systems. Definitely not true. Every bit of memory that's not available that could be shared memory instead is a reduction in memory available for filesystem caches, etc. As for "high multi-tenancy" there's nobody out there with server occupancy as high as Google's (see the recent Borg scheduler traces for concrete data) and they statically link everything. Cloud vendor computing models are not generally the computing model of the rest of the world. Comparison to their environment is not relevant to the general populace. I worked for a "big iron" OEM vendor until late 2017 and the savings were definitely still significant then both for their customers and the vendor themselves. There are numerous benefits to shared linking, that doesn't mean it's always the appropriate solution, but is not correct to claim that there are no performance benefits. Especially on more memory-constrained consumer devices, the shared memory benefits of dynamic linking are still significantly beneficial.
- danans 6y ago
  > Cloud vendor computing models are not generally the computing model of the rest of the world. > Comparison to their environment is not relevant to the general populace. The way that Google shares server compute and memory resources is by having a service oriented architecture. A single high scale service serves many different applications, usually colocated in the same cluster or data center. Each service is based on multiple instances of a statically linked binary. At that scale, there is no point in try to use shared dynamically linked libraries to reduce consumption because you save more by either reducing increasing your own app's efficiency or relying on one of the major services rather than linking more functionality into your own app.
  - binarycrusader 6y ago
    I'm aware, which is why I specifically said that cloud vendor computing models aren't really relevant to the general populace. Google's model in particular is (or at least was) very different from other vendors.
    - jeffbee 6y ago
      I don't disagree with your point that use cases vary, but when I hear people say that "only clouds need this" I think the speaker is underestimating the size of cloud facilities. The amount of the world's computers that are in Amazon's, Google's, Facebook's, and Microsoft's clouds is a huge chunk of the total.