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GPU Poisson Solver

Background

This solver solves the Poisson equation on a cubical domain, $\Omega$, for a specific set of boundary conditions. The poisson equation can be expressed as

$$\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} + \frac{\partial^2 u}{\partial z^2} = -f(x,y,z), \quad (x,y,x) \in \Omega$$

with, for this problem, a boundary defined by

$$\Omega = \{(x, y, z) : |x| \leq 1, |y| \leq 1, |z| \leq 1\}$$

and boundary conditions

$$\begin{align*} u(x, 1, z) &= 20, u(x, -1, z) = 0, -1 \leq x, z \leq 1 \\\ u(1, y, z) &= u(-1, y, z) = 20, -1 \leq y, z \leq 1 \\\ u(x, y, -1) &= u(x, y, 1) = 20, -1 \leq x, y \leq 1. \end{align*}$$

The purpose of the solver is to compare performance across different parallelization methods and includes parallel methods for:

  • CPU (parallel)
  • Single-GPU via OpenMP
  • Dual-GPU via OpenMP
  • Single-GPU via CUDA
  • Dual-GPU via CUDA
  • Four-GPU (two nodes, each with two GPUs), via CUDA, OpenMPI, and NCCL

A full writeup is available in the report.

Requirements

The project is compiled with the mpic++ compiler, an OpenMPI C++ wrapper compiler. The underlying compiler is set to nvc++, NVIDIA's compiler for their GPUS. This can be done by setting the environment variable OMPI_CXX to nvc++ via

export OMPI_CXX=nvc++

Other requirements include:

  • CUDA
  • OpenMPI
  • OpenMP
  • NCCL

Executable

The driver executable can be called as follows

./poisson_solver N K T_0 output_type method [file_suffix] [threads]

N: Problem size. For single-GPU solvers, this needs to be a multiple of 16. For the dual-GPU CUDA solver, this needs to be a multiple of 32.

K: Number of iterations.

T_0: Starting temeprature of inner points on the domain, in Kelvin.

output_type:

  • 0 = No output
  • 1 = Performance metrics printed as [N] [wall time] [data transfer time (s)] [memory (MB)] [bandwidth (data transfer, GB/s)] [bandwidth (no data transfer, GB/s)] [time spent in kernel (s, not always measured)] [bandwidth based on kernel time (s, not always measured)]
  • 3 = Write binary dump (.bin)
  • 4 = Write .vtk file

method:

  • 1 = CPU parallel solver. Number of threads can be specified with the threads argument
  • 2 = Single-GPU solver using OpenMP
  • 3 = Dual-GPU solver using OpenMP
  • 4 = Single-GPU solver using CUDA
  • 5 = Single-GPU solver using CUDA, improved memory access patterns
  • 6 = Dual-GPU solver using CUDA
  • 7 = Four-GPU solver using CUDA+NCCL+MPI. This solver assumes each available node has two GPUs.

file_suffix: Suffix to add to .vtk file

threads: Threads for CPU versions

About

3D accelerated poisson solver for distributed systems

Resources

Readme
Activity

Stars

4 stars

Watchers

1 watching

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0 forks
Report repository

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GPU Poisson Solver
Background
This solver solves the Poisson equation on a cubical domain, $\Omega$, for a specific set of boundary conditions. The poisson equation can be expressed as
$$\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} + \frac{\partial^2 u}{\partial z^2} = -f(x,y,z), \quad (x,y,x) \in \Omega$$
with, for this problem, a boundary defined by
$$\Omega = \{(x, y, z) : |x| \leq 1, |y| \leq 1, |z| \leq 1\}$$
and boundary conditions
$$\begin{align*}
u(x, 1, z) &= 20, u(x, -1, z) = 0, -1 \leq x, z \leq 1 \\\
u(1, y, z) &= u(-1, y, z) = 20, -1 \leq y, z \leq 1 \\\
u(x, y, -1) &= u(x, y, 1) = 20, -1 \leq x, y \leq 1.
\end{align*}$$
The purpose of the solver is to compare performance across different parallelization methods and includes parallel methods for:
  • CPU (parallel)
  • Single-GPU via OpenMP
  • Dual-GPU via OpenMP
  • Single-GPU via CUDA
  • Dual-GPU via CUDA
  • Four-GPU (two nodes, each with two GPUs), via CUDA, OpenMPI, and NCCL
A full writeup is available in the report.
Requirements
The project is compiled with the mpic++ compiler, an OpenMPI C++ wrapper compiler. The underlying compiler is set to nvc++, NVIDIA's compiler for their GPUS. This can be done by setting the environment variable OMPI_CXX to nvc++ via
export OMPI_CXX=nvc++

Other requirements include:
  • CUDA
  • OpenMPI
  • OpenMP
  • NCCL
Executable
The driver executable can be called as follows
./poisson_solver N K T_0 output_type method [file_suffix] [threads]

N: Problem size. For single-GPU solvers, this needs to be a multiple of 16. For the dual-GPU CUDA solver, this needs to be a multiple of 32.
K: Number of iterations.
T_0: Starting temeprature of inner points on the domain, in Kelvin.
output_type:
  • 0 = No output
  • 1 = Performance metrics printed as [N] [wall time] [data transfer time (s)] [memory (MB)] [bandwidth (data transfer, GB/s)] [bandwidth (no data transfer, GB/s)] [time spent in kernel (s, not always measured)] [bandwidth based on kernel time (s, not always measured)]
  • 3 = Write binary dump (.bin)
  • 4 = Write .vtk file
method:
  • 1 = CPU parallel solver. Number of threads can be specified with the threads argument
  • 2 = Single-GPU solver using OpenMP
  • 3 = Dual-GPU solver using OpenMP
  • 4 = Single-GPU solver using CUDA
  • 5 = Single-GPU solver using CUDA, improved memory access patterns
  • 6 = Dual-GPU solver using CUDA
  • 7 = Four-GPU solver using CUDA+NCCL+MPI. This solver assumes each available node has two GPUs.
file_suffix: Suffix to add to .vtk file
threads: Threads for CPU versions
About
3D accelerated poisson solver for distributed systems
Resources
Readme
Activity
Stars
4 stars
Watchers
1 watching
Forks
0 forks
Report repository
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Repository files navigation
GPU Poisson Solver
Background
This solver solves the Poisson equation on a cubical domain, $\Omega$, for a specific set of boundary conditions. The poisson equation can be expressed as
$$\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} + \frac{\partial^2 u}{\partial z^2} = -f(x,y,z), \quad (x,y,x) \in \Omega$$
with, for this problem, a boundary defined by
$$\Omega = \{(x, y, z) : |x| \leq 1, |y| \leq 1, |z| \leq 1\}$$
and boundary conditions
$$\begin{align*}
u(x, 1, z) &= 20, u(x, -1, z) = 0, -1 \leq x, z \leq 1 \\\
u(1, y, z) &= u(-1, y, z) = 20, -1 \leq y, z \leq 1 \\\
u(x, y, -1) &= u(x, y, 1) = 20, -1 \leq x, y \leq 1.
\end{align*}$$
The purpose of the solver is to compare performance across different parallelization methods and includes parallel methods for:
  • CPU (parallel)
  • Single-GPU via OpenMP
  • Dual-GPU via OpenMP
  • Single-GPU via CUDA
  • Dual-GPU via CUDA
  • Four-GPU (two nodes, each with two GPUs), via CUDA, OpenMPI, and NCCL
A full writeup is available in the report.
Requirements
The project is compiled with the mpic++ compiler, an OpenMPI C++ wrapper compiler. The underlying compiler is set to nvc++, NVIDIA's compiler for their GPUS. This can be done by setting the environment variable OMPI_CXX to nvc++ via
export OMPI_CXX=nvc++

Other requirements include:
  • CUDA
  • OpenMPI
  • OpenMP
  • NCCL
Executable
The driver executable can be called as follows
./poisson_solver N K T_0 output_type method [file_suffix] [threads]

N: Problem size. For single-GPU solvers, this needs to be a multiple of 16. For the dual-GPU CUDA solver, this needs to be a multiple of 32.
K: Number of iterations.
T_0: Starting temeprature of inner points on the domain, in Kelvin.
output_type:
  • 0 = No output
  • 1 = Performance metrics printed as [N] [wall time] [data transfer time (s)] [memory (MB)] [bandwidth (data transfer, GB/s)] [bandwidth (no data transfer, GB/s)] [time spent in kernel (s, not always measured)] [bandwidth based on kernel time (s, not always measured)]
  • 3 = Write binary dump (.bin)
  • 4 = Write .vtk file
method:
  • 1 = CPU parallel solver. Number of threads can be specified with the threads argument
  • 2 = Single-GPU solver using OpenMP
  • 3 = Dual-GPU solver using OpenMP
  • 4 = Single-GPU solver using CUDA
  • 5 = Single-GPU solver using CUDA, improved memory access patterns
  • 6 = Dual-GPU solver using CUDA
  • 7 = Four-GPU solver using CUDA+NCCL+MPI. This solver assumes each available node has two GPUs.
file_suffix: Suffix to add to .vtk file
threads: Threads for CPU versions
About
3D accelerated poisson solver for distributed systems
Resources
Readme
Activity
Stars
4 stars
Watchers
1 watching
Forks
0 forks
Report repository
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Repository files navigation
GPU Poisson Solver
Background
This solver solves the Poisson equation on a cubical domain, $\Omega$, for a specific set of boundary conditions. The poisson equation can be expressed as
$$\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} + \frac{\partial^2 u}{\partial z^2} = -f(x,y,z), \quad (x,y,x) \in \Omega$$
with, for this problem, a boundary defined by
$$\Omega = \{(x, y, z) : |x| \leq 1, |y| \leq 1, |z| \leq 1\}$$
and boundary conditions
$$\begin{align*}
u(x, 1, z) &= 20, u(x, -1, z) = 0, -1 \leq x, z \leq 1 \\\
u(1, y, z) &= u(-1, y, z) = 20, -1 \leq y, z \leq 1 \\\
u(x, y, -1) &= u(x, y, 1) = 20, -1 \leq x, y \leq 1.
\end{align*}$$
The purpose of the solver is to compare performance across different parallelization methods and includes parallel methods for:
  • CPU (parallel)
  • Single-GPU via OpenMP
  • Dual-GPU via OpenMP
  • Single-GPU via CUDA
  • Dual-GPU via CUDA
  • Four-GPU (two nodes, each with two GPUs), via CUDA, OpenMPI, and NCCL
A full writeup is available in the report.
Requirements
The project is compiled with the mpic++ compiler, an OpenMPI C++ wrapper compiler. The underlying compiler is set to nvc++, NVIDIA's compiler for their GPUS. This can be done by setting the environment variable OMPI_CXX to nvc++ via
export OMPI_CXX=nvc++

Other requirements include:
  • CUDA
  • OpenMPI
  • OpenMP
  • NCCL
Executable
The driver executable can be called as follows
./poisson_solver N K T_0 output_type method [file_suffix] [threads]

N: Problem size. For single-GPU solvers, this needs to be a multiple of 16. For the dual-GPU CUDA solver, this needs to be a multiple of 32.
K: Number of iterations.
T_0: Starting temeprature of inner points on the domain, in Kelvin.
output_type:
  • 0 = No output
  • 1 = Performance metrics printed as [N] [wall time] [data transfer time (s)] [memory (MB)] [bandwidth (data transfer, GB/s)] [bandwidth (no data transfer, GB/s)] [time spent in kernel (s, not always measured)] [bandwidth based on kernel time (s, not always measured)]
  • 3 = Write binary dump (.bin)
  • 4 = Write .vtk file
method:
  • 1 = CPU parallel solver. Number of threads can be specified with the threads argument
  • 2 = Single-GPU solver using OpenMP
  • 3 = Dual-GPU solver using OpenMP
  • 4 = Single-GPU solver using CUDA
  • 5 = Single-GPU solver using CUDA, improved memory access patterns
  • 6 = Dual-GPU solver using CUDA
  • 7 = Four-GPU solver using CUDA+NCCL+MPI. This solver assumes each available node has two GPUs.
file_suffix: Suffix to add to .vtk file
threads: Threads for CPU versions
About
3D accelerated poisson solver for distributed systems
Resources
Readme
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Stars
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Watchers
1 watching
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0 forks
Report repository
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Repository files navigation
GPU Poisson Solver
Background
This solver solves the Poisson equation on a cubical domain, $\Omega$, for a specific set of boundary conditions. The poisson equation can be expressed as
$$\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} + \frac{\partial^2 u}{\partial z^2} = -f(x,y,z), \quad (x,y,x) \in \Omega$$
with, for this problem, a boundary defined by
$$\Omega = \{(x, y, z) : |x| \leq 1, |y| \leq 1, |z| \leq 1\}$$
and boundary conditions
$$\begin{align*}
u(x, 1, z) &= 20, u(x, -1, z) = 0, -1 \leq x, z \leq 1 \\\
u(1, y, z) &= u(-1, y, z) = 20, -1 \leq y, z \leq 1 \\\
u(x, y, -1) &= u(x, y, 1) = 20, -1 \leq x, y \leq 1.
\end{align*}$$
The purpose of the solver is to compare performance across different parallelization methods and includes parallel methods for:
  • CPU (parallel)
  • Single-GPU via OpenMP
  • Dual-GPU via OpenMP
  • Single-GPU via CUDA
  • Dual-GPU via CUDA
  • Four-GPU (two nodes, each with two GPUs), via CUDA, OpenMPI, and NCCL
A full writeup is available in the report.
Requirements
The project is compiled with the mpic++ compiler, an OpenMPI C++ wrapper compiler. The underlying compiler is set to nvc++, NVIDIA's compiler for their GPUS. This can be done by setting the environment variable OMPI_CXX to nvc++ via
export OMPI_CXX=nvc++

Other requirements include:
  • CUDA
  • OpenMPI
  • OpenMP
  • NCCL
Executable
The driver executable can be called as follows
./poisson_solver N K T_0 output_type method [file_suffix] [threads]

N: Problem size. For single-GPU solvers, this needs to be a multiple of 16. For the dual-GPU CUDA solver, this needs to be a multiple of 32.
K: Number of iterations.
T_0: Starting temeprature of inner points on the domain, in Kelvin.
output_type:
  • 0 = No output
  • 1 = Performance metrics printed as [N] [wall time] [data transfer time (s)] [memory (MB)] [bandwidth (data transfer, GB/s)] [bandwidth (no data transfer, GB/s)] [time spent in kernel (s, not always measured)] [bandwidth based on kernel time (s, not always measured)]
  • 3 = Write binary dump (.bin)
  • 4 = Write .vtk file
method:
  • 1 = CPU parallel solver. Number of threads can be specified with the threads argument
  • 2 = Single-GPU solver using OpenMP
  • 3 = Dual-GPU solver using OpenMP
  • 4 = Single-GPU solver using CUDA
  • 5 = Single-GPU solver using CUDA, improved memory access patterns
  • 6 = Dual-GPU solver using CUDA
  • 7 = Four-GPU solver using CUDA+NCCL+MPI. This solver assumes each available node has two GPUs.
file_suffix: Suffix to add to .vtk file
threads: Threads for CPU versions
About
3D accelerated poisson solver for distributed systems
Resources
Readme
Activity
Stars
4 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
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GPU Poisson Solver
Background
This solver solves the Poisson equation on a cubical domain, $\Omega$, for a specific set of boundary conditions. The poisson equation can be expressed as
$$\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} + \frac{\partial^2 u}{\partial z^2} = -f(x,y,z), \quad (x,y,x) \in \Omega$$
with, for this problem, a boundary defined by
$$\Omega = \{(x, y, z) : |x| \leq 1, |y| \leq 1, |z| \leq 1\}$$
and boundary conditions
$$\begin{align*}
u(x, 1, z) &= 20, u(x, -1, z) = 0, -1 \leq x, z \leq 1 \\\
u(1, y, z) &= u(-1, y, z) = 20, -1 \leq y, z \leq 1 \\\
u(x, y, -1) &= u(x, y, 1) = 20, -1 \leq x, y \leq 1.
\end{align*}$$
The purpose of the solver is to compare performance across different parallelization methods and includes parallel methods for:
  • CPU (parallel)
  • Single-GPU via OpenMP
  • Dual-GPU via OpenMP
  • Single-GPU via CUDA
  • Dual-GPU via CUDA
  • Four-GPU (two nodes, each with two GPUs), via CUDA, OpenMPI, and NCCL
A full writeup is available in the report.
Requirements
The project is compiled with the mpic++ compiler, an OpenMPI C++ wrapper compiler. The underlying compiler is set to nvc++, NVIDIA's compiler for their GPUS. This can be done by setting the environment variable OMPI_CXX to nvc++ via
export OMPI_CXX=nvc++

Other requirements include:
  • CUDA
  • OpenMPI
  • OpenMP
  • NCCL
Executable
The driver executable can be called as follows
./poisson_solver N K T_0 output_type method [file_suffix] [threads]

N: Problem size. For single-GPU solvers, this needs to be a multiple of 16. For the dual-GPU CUDA solver, this needs to be a multiple of 32.
K: Number of iterations.
T_0: Starting temeprature of inner points on the domain, in Kelvin.
output_type:
  • 0 = No output
  • 1 = Performance metrics printed as [N] [wall time] [data transfer time (s)] [memory (MB)] [bandwidth (data transfer, GB/s)] [bandwidth (no data transfer, GB/s)] [time spent in kernel (s, not always measured)] [bandwidth based on kernel time (s, not always measured)]
  • 3 = Write binary dump (.bin)
  • 4 = Write .vtk file
method:
  • 1 = CPU parallel solver. Number of threads can be specified with the threads argument
  • 2 = Single-GPU solver using OpenMP
  • 3 = Dual-GPU solver using OpenMP
  • 4 = Single-GPU solver using CUDA
  • 5 = Single-GPU solver using CUDA, improved memory access patterns
  • 6 = Dual-GPU solver using CUDA
  • 7 = Four-GPU solver using CUDA+NCCL+MPI. This solver assumes each available node has two GPUs.
file_suffix: Suffix to add to .vtk file
threads: Threads for CPU versions
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3D accelerated poisson solver for distributed systems
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GitHub - LukeLabrie/gpu_poisson_solver: 3D accelerated poisson solver for distributed systems · GitHub
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GPU Poisson Solver
Background
This solver solves the Poisson equation on a cubical domain, $\Omega$, for a specific set of boundary conditions. The poisson equation can be expressed as
$$\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} + \frac{\partial^2 u}{\partial z^2} = -f(x,y,z), \quad (x,y,x) \in \Omega$$
with, for this problem, a boundary defined by
$$\Omega = \{(x, y, z) : |x| \leq 1, |y| \leq 1, |z| \leq 1\}$$
and boundary conditions
$$\begin{align*}
u(x, 1, z) &= 20, u(x, -1, z) = 0, -1 \leq x, z \leq 1 \\\
u(1, y, z) &= u(-1, y, z) = 20, -1 \leq y, z \leq 1 \\\
u(x, y, -1) &= u(x, y, 1) = 20, -1 \leq x, y \leq 1.
\end{align*}$$
The purpose of the solver is to compare performance across different parallelization methods and includes parallel methods for:
  • CPU (parallel)
  • Single-GPU via OpenMP
  • Dual-GPU via OpenMP
  • Single-GPU via CUDA
  • Dual-GPU via CUDA
  • Four-GPU (two nodes, each with two GPUs), via CUDA, OpenMPI, and NCCL
A full writeup is available in the report.
Requirements
The project is compiled with the mpic++ compiler, an OpenMPI C++ wrapper compiler. The underlying compiler is set to nvc++, NVIDIA's compiler for their GPUS. This can be done by setting the environment variable OMPI_CXX to nvc++ via
export OMPI_CXX=nvc++

Other requirements include:
  • CUDA
  • OpenMPI
  • OpenMP
  • NCCL
Executable
The driver executable can be called as follows
./poisson_solver N K T_0 output_type method [file_suffix] [threads]

N: Problem size. For single-GPU solvers, this needs to be a multiple of 16. For the dual-GPU CUDA solver, this needs to be a multiple of 32.
K: Number of iterations.
T_0: Starting temeprature of inner points on the domain, in Kelvin.
output_type:
  • 0 = No output
  • 1 = Performance metrics printed as [N] [wall time] [data transfer time (s)] [memory (MB)] [bandwidth (data transfer, GB/s)] [bandwidth (no data transfer, GB/s)] [time spent in kernel (s, not always measured)] [bandwidth based on kernel time (s, not always measured)]
  • 3 = Write binary dump (.bin)
  • 4 = Write .vtk file
method:
  • 1 = CPU parallel solver. Number of threads can be specified with the threads argument
  • 2 = Single-GPU solver using OpenMP
  • 3 = Dual-GPU solver using OpenMP
  • 4 = Single-GPU solver using CUDA
  • 5 = Single-GPU solver using CUDA, improved memory access patterns
  • 6 = Dual-GPU solver using CUDA
  • 7 = Four-GPU solver using CUDA+NCCL+MPI. This solver assumes each available node has two GPUs.
file_suffix: Suffix to add to .vtk file
threads: Threads for CPU versions
About
3D accelerated poisson solver for distributed systems
Resources
Readme
Activity
Stars
4 stars
Watchers
1 watching
Forks
0 forks
Report repository
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Packages
Contributors
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GitHub - LukeLabrie/gpu_poisson_solver: 3D accelerated poisson solver for distributed systems · GitHub
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Repository files navigation
GPU Poisson Solver
Background
This solver solves the Poisson equation on a cubical domain, $\Omega$, for a specific set of boundary conditions. The poisson equation can be expressed as
$$\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} + \frac{\partial^2 u}{\partial z^2} = -f(x,y,z), \quad (x,y,x) \in \Omega$$
with, for this problem, a boundary defined by
$$\Omega = \{(x, y, z) : |x| \leq 1, |y| \leq 1, |z| \leq 1\}$$
and boundary conditions
$$\begin{align*}
u(x, 1, z) &= 20, u(x, -1, z) = 0, -1 \leq x, z \leq 1 \\\
u(1, y, z) &= u(-1, y, z) = 20, -1 \leq y, z \leq 1 \\\
u(x, y, -1) &= u(x, y, 1) = 20, -1 \leq x, y \leq 1.
\end{align*}$$
The purpose of the solver is to compare performance across different parallelization methods and includes parallel methods for:
  • CPU (parallel)
  • Single-GPU via OpenMP
  • Dual-GPU via OpenMP
  • Single-GPU via CUDA
  • Dual-GPU via CUDA
  • Four-GPU (two nodes, each with two GPUs), via CUDA, OpenMPI, and NCCL
A full writeup is available in the report.
Requirements
The project is compiled with the mpic++ compiler, an OpenMPI C++ wrapper compiler. The underlying compiler is set to nvc++, NVIDIA's compiler for their GPUS. This can be done by setting the environment variable OMPI_CXX to nvc++ via
export OMPI_CXX=nvc++

Other requirements include:
  • CUDA
  • OpenMPI
  • OpenMP
  • NCCL
Executable
The driver executable can be called as follows
./poisson_solver N K T_0 output_type method [file_suffix] [threads]

N: Problem size. For single-GPU solvers, this needs to be a multiple of 16. For the dual-GPU CUDA solver, this needs to be a multiple of 32.
K: Number of iterations.
T_0: Starting temeprature of inner points on the domain, in Kelvin.
output_type:
  • 0 = No output
  • 1 = Performance metrics printed as [N] [wall time] [data transfer time (s)] [memory (MB)] [bandwidth (data transfer, GB/s)] [bandwidth (no data transfer, GB/s)] [time spent in kernel (s, not always measured)] [bandwidth based on kernel time (s, not always measured)]
  • 3 = Write binary dump (.bin)
  • 4 = Write .vtk file
method:
  • 1 = CPU parallel solver. Number of threads can be specified with the threads argument
  • 2 = Single-GPU solver using OpenMP
  • 3 = Dual-GPU solver using OpenMP
  • 4 = Single-GPU solver using CUDA
  • 5 = Single-GPU solver using CUDA, improved memory access patterns
  • 6 = Dual-GPU solver using CUDA
  • 7 = Four-GPU solver using CUDA+NCCL+MPI. This solver assumes each available node has two GPUs.
file_suffix: Suffix to add to .vtk file
threads: Threads for CPU versions
About
3D accelerated poisson solver for distributed systems
Resources
Readme
Activity
Stars
4 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages