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It's wonderful that the entire paper is available freely from the journal. Most journals these days are pay-for-access (and none of the payment makes it to the

It's wonderful that the entire paper is available freely from the journal. Most journals these days are pay-for-access (and none of the payment makes it to the authors).

ramraj07 5y ago
Could be wrong but it’s possible the authors had to pay tens of thousands to make it free.
- anon946 5y ago
  Looks like about $10K. https://www.cell.com/open-access https://www.cell.com/open-access
- brnaftr361 5y ago
  NVIDIA published a headline on their site. I could imagine them bankrolling the open publication. Good PR, good science it's a win-win and a trivial expense. https://blogs.nvidia.com/blog/2022/01/20/living-cell-simulation/?nvid=nv-int-csfg-570700#cid=gnl_nv-int-csfg_en-us https://blogs.nvidia.com/blog/2022/01/20/living-cell-simulat...
  - Fomite 5y ago
    NVIDIA has GPU grants for research.
    - dekhn 5y ago
      schulten, the author of the paper, has been well funded at UIUC for decades. These sorts of simulations are Schulten's area and she's well funded (her husand is also there and is also well-funded, with near-infinite compute resources available). It's unlikely that schulten would bother with a small grant, leaving that more for starting-up investigators who can't afford more hardware.
      - Fomite 5y ago
        I mean, I applied for one despite my lab being very well funded, it was maybe 30 minutes worth of work? But that was merely a note for "How this could have gotten on Nvidia's site" that isn't "Nvidia paid for it all."
Animats 5y ago
The code is on Github: https://github.com/Luthey-Schulten-Lab/Minimal_Cell https://github.com/Luthey-Schulten-Lab/Minimal_Cell https://github.com/Luthey-Schulten-Lab/Lattice_Microbes https://github.com/Luthey-Schulten-Lab/Lattice_Microbes This is an impressive result. They've found a nice level at which to simulate. Down at the atom level would take too long. They got this to work at the chemical reaction in 3D space level, low enough that the model maps directly to the biochemistry. They don't seem to say how many GPUs they used, but the article seems to indicate small numbers, not entire data centers. Current speed is about 1/30 of real time for one minimal cell, which is pretty good.
- _Nat_ 5y ago
  Looks like they used up to 1 GPU per simulation: > The GPUs used for spatial simulations included NVIDIA Titan V and NVIDIA Tesla Volta V100 GPUs, which took 10 h and 8 h to simulate 20 min of cell time, respectively. So apparently they tried 3 different GPU configurations: 1. A single Nvidia Titan V, for a non-mixed model, which took 10-hours to simulate 20-minutes. 2. A single Nvidia Tesla Volta V100, for a non-mixed model, which took 8-hours to simulate 20-minutes. 3. No GPU's, for a well-mixed model. Regarding mixing: A well-mixed model is one where all chemicals are assumed to have spatially-equal concentrations throughout a phase. By contrast, a non-mixed ("spatially resolved", in the paper) model models chemicals as having concentrations that can vary from location to location, making them more realistic but also far more expensive. For anyone surprised that they only needed up to 1 GPU per simulation: their models appeared to be largely based in rate-kinetics; it's not like they were simulating atoms or really even molecules, but rather more like they were simulating concentrations of molecules. To note it, they probably couldn't get a linear-speedup by using more GPU's. The thing's that they needed the GPU's to solve interactions over a space; if they had multiple GPU's, then they'd have needed to actively connect them on each iteration, slowing down the simulations. For a small number of GPU's (like maybe 2 to 4), they might try for a near-linear speedup if they fudge the boundaries a bit (allowing computational-artifacts at the edges between them).
  - Animats 5y ago
    That sounds good. So single-cell simulation needs only a modest level of hardware. When simulation progresses to multicellular organisms, inter-cell connections can probably be done less frequently, over a network. C. Elegans, the nematode worm that's the minimum viable heavily studied organism, has 959 cells. A thousand GPUs is not an out of reach number. Just a big cloud bill.

It's wonderful that the entire paper is available freely from the journal. Most journals these days are pay-for-access (and none of the payment makes it to the authors).

ramraj07 5y ago

Could be wrong but it’s possible the authors had to pay tens of thousands to make it free.

anon946 5y ago
Looks like about $10K. https://www.cell.com/open-access https://www.cell.com/open-access
brnaftr361 5y ago
NVIDIA published a headline on their site. I could imagine them bankrolling the open publication. Good PR, good science it's a win-win and a trivial expense. https://blogs.nvidia.com/blog/2022/01/20/living-cell-simulation/?nvid=nv-int-csfg-570700#cid=gnl_nv-int-csfg_en-us https://blogs.nvidia.com/blog/2022/01/20/living-cell-simulat...
- Fomite 5y ago
  NVIDIA has GPU grants for research.
  - dekhn 5y ago
    schulten, the author of the paper, has been well funded at UIUC for decades. These sorts of simulations are Schulten's area and she's well funded (her husand is also there and is also well-funded, with near-infinite compute resources available). It's unlikely that schulten would bother with a small grant, leaving that more for starting-up investigators who can't afford more hardware.
    - Fomite 5y ago
      I mean, I applied for one despite my lab being very well funded, it was maybe 30 minutes worth of work? But that was merely a note for "How this could have gotten on Nvidia's site" that isn't "Nvidia paid for it all."

Animats 5y ago

The code is on Github: https://github.com/Luthey-Schulten-Lab/Minimal_Cell https://github.com/Luthey-Schulten-Lab/Minimal_Cell https://github.com/Luthey-Schulten-Lab/Lattice_Microbes https://github.com/Luthey-Schulten-Lab/Lattice_Microbes This is an impressive result. They've found a nice level at which to simulate. Down at the atom level would take too long. They got this to work at the chemical reaction in 3D space level, low enough that the model maps directly to the biochemistry. They don't seem to say how many GPUs they used, but the article seems to indicate small numbers, not entire data centers. Current speed is about 1/30 of real time for one minimal cell, which is pretty good.

_Nat_ 5y ago
Looks like they used up to 1 GPU per simulation: > The GPUs used for spatial simulations included NVIDIA Titan V and NVIDIA Tesla Volta V100 GPUs, which took 10 h and 8 h to simulate 20 min of cell time, respectively. So apparently they tried 3 different GPU configurations: 1. A single Nvidia Titan V, for a non-mixed model, which took 10-hours to simulate 20-minutes. 2. A single Nvidia Tesla Volta V100, for a non-mixed model, which took 8-hours to simulate 20-minutes. 3. No GPU's, for a well-mixed model. Regarding mixing: A well-mixed model is one where all chemicals are assumed to have spatially-equal concentrations throughout a phase. By contrast, a non-mixed ("spatially resolved", in the paper) model models chemicals as having concentrations that can vary from location to location, making them more realistic but also far more expensive. For anyone surprised that they only needed up to 1 GPU per simulation: their models appeared to be largely based in rate-kinetics; it's not like they were simulating atoms or really even molecules, but rather more like they were simulating concentrations of molecules. To note it, they probably couldn't get a linear-speedup by using more GPU's. The thing's that they needed the GPU's to solve interactions over a space; if they had multiple GPU's, then they'd have needed to actively connect them on each iteration, slowing down the simulations. For a small number of GPU's (like maybe 2 to 4), they might try for a near-linear speedup if they fudge the boundaries a bit (allowing computational-artifacts at the edges between them).
- Animats 5y ago
  That sounds good. So single-cell simulation needs only a modest level of hardware. When simulation progresses to multicellular organisms, inter-cell connections can probably be done less frequently, over a network. C. Elegans, the nematode worm that's the minimum viable heavily studied organism, has 959 cells. A thousand GPUs is not an out of reach number. Just a big cloud bill.