From a082040333d29d62260ec55933c69be7331f0606 Mon Sep 17 00:00:00 2001
From: cs123n <liuluping1119@gmail.com>
Date: Sun, 29 May 2022 08:00:18 +0800
Subject: [PATCH] add readme

---
 .gitignore       |  1 +
 input/func.py    |  5 +++--
 main.py          |  1 +
 readme.md        | 18 ++++++++++++++++++
 requirements.txt |  1 +
 test/smooth.py   | 35 -----------------------------------
 test/test.py     | 33 ---------------------------------
 test/test1.py    | 20 --------------------
 8 files changed, 24 insertions(+), 90 deletions(-)
 create mode 100644 readme.md
 create mode 100644 requirements.txt
 delete mode 100644 test/smooth.py
 delete mode 100644 test/test.py
 delete mode 100644 test/test1.py

diff --git a/.gitignore b/.gitignore
index 0d20b64..d601571 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1 +1,2 @@
 *.pyc
+test
diff --git a/input/func.py b/input/func.py
index 3b17b01..e0e9012 100644
--- a/input/func.py
+++ b/input/func.py
@@ -1,7 +1,8 @@
 import torch as th
 
 def origin_func(x, y):
-    return - 2 * th.exp(x + y) #* (th.sin(x) * th.sin(y) - th.cos(x) * th.cos(y))
+    # return - 2 * th.exp(x + y) * (th.cos(x) * th.cos(y) - th.sin(x) * th.sin(y))
+    return - 2 * th.exp(x + y) * th.cos(x + y)
 
 def target_func(x, y):
-    return th.exp(x + y) #* th.cos(x) * th.sin(y)
+    return th.exp(x + y) * th.cos(x) * th.sin(y)
diff --git a/main.py b/main.py
index 2094670..c41f196 100644
--- a/main.py
+++ b/main.py
@@ -42,6 +42,7 @@
     if rank == 0:
         print(u.view(w, w)[:8, :8])
 
+
     # if rank == 3:
     #     print(u.view(w, w)[0:8, 0:8])
 
diff --git a/readme.md b/readme.md
new file mode 100644
index 0000000..74d1e67
--- /dev/null
+++ b/readme.md
@@ -0,0 +1,18 @@
+# MultiGrid Method
+
+Hi, everyone! This repo provides a parallel version of 2-D multigrid method based on Pytorch.
+
+Install necessary python packages:
+```bash
+pip install -r requirements.txt
+```
+
+Run single node version:
+```bash
+python main.py -n 64 -p 1
+```
+
+Run multi-node version:
+```bash
+torchrun --nproc_per_node 4 main.py -n 64 -p 2
+```
\ No newline at end of file
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..713f0b5
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1 @@
+torch>=1.10.0
diff --git a/test/smooth.py b/test/smooth.py
deleted file mode 100644
index 7584b11..0000000
--- a/test/smooth.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import torch as th
-import math
-
-
-def separate(A):
-    return th.diag(A), -th.tril(A, -1), -th.triu(A, 1)
-
-def smooth(A, w=2.0/3, type='jacobi'):
-    D, L, U = separate(A)
-    if type == 'jacobi':
-        Di = (1 / D)
-        T, c_ = Di * (L + U), lambda b: Di * b
-    else:
-        T, c_ = None, None
-
-    def method(x, b, m):
-        c = c_(b)
-        for _ in range(m):
-            x = w * (T @ x + c) + (1 - w) * x 
-        return x
-    return method
-
-
-if __name__ == "__main__":
-    from grid import tridiag
-
-    n = 4
-    A, b = tridiag(-1, 2, -1, n, device='cpu'), th.randn(n)
-    x = th.inverse(A) @ b
-
-    smooth_method = smooth(A, w=2.0/3)
-    x_p = smooth_method(th.zeros(n), b, 10)
-    # print(x)
-
-
diff --git a/test/test.py b/test/test.py
deleted file mode 100644
index 4e3a65d..0000000
--- a/test/test.py
+++ /dev/null
@@ -1,33 +0,0 @@
-import torch as th
-import argparse
-import time
-
-from grid import laplace, condition
-from multigrid import MultiGrid, FullMultiGrid
-from input.func import origin_func, target_func
-from smooth import smooth
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    # parser.add_argument('--n', '-n', type=int, default=16)
-    parser.add_argument('--device', type=str, default='cpu')
-    args = parser.parse_args()
-
-    device = th.device(args.device)
-    e_list = []
-    for n in (8, 16, 32, 64, 128):
-    
-        A = laplace(n, device)[n]
-        MG_method = MultiGrid(n, device)
-        b_method = condition(n, device)
-        b, u_t = b_method(origin_func, target_func)  # condition(origin_func)
-
-        u = th.zeros((n-1)**2, device=device)
-        for _ in range(n):
-            u = MG_method(u, b, n=n)
-        e_list.append(th.norm(u - u_t) / n)
-
-    o_list = [th.log2(e_list[i]) - th.log2(e_list[i+1]) for i in range(len(e_list)-1)]
-    print(e_list)
-    print(o_list)
\ No newline at end of file
diff --git a/test/test1.py b/test/test1.py
deleted file mode 100644
index 6232d81..0000000
--- a/test/test1.py
+++ /dev/null
@@ -1,20 +0,0 @@
-import torch as th
-import torch.nn.functional as F
-import torch.distributed as dist
-import sys
-import os
-
-
-rank = os.environ.get("LOCAL_RANK")
-rank = 0 if rank is None else int(rank)
-dist.init_process_group(backend='gloo')
-
-s_list = th.tensor([1., 2.])
-s_list = [item.reshape(1, 1) for item in s_list]
-s = th.zeros(1)
-if rank == 0:
-    dist.scatter(s, s_list)
-else:
-    dist.scatter(s)
-
-print(s)