Hugging Face's logo

Spaces:
Elfsong
/
gcp_allocator
Sleeping

App Files Community
Du Mingzhe commited on
Commit
b34636e
·
1 Parent(s): 88be439

update

Browse files
Files changed (1) hide show
  1. app.py +20 -124
app.py CHANGED
@@ -2,130 +2,26 @@ import streamlit as st
2
 
3
  st.title("GCP Resource Alloctor")
4
 
5
- # GPU Type
6
- gpu_type = st.selectbox(
7
- 'Which type of GPU you would like to use?',
8
- (
9
- 'NVIDIA H100 80GB',
10
- 'NVIDIA A100 80GB',
11
- 'NVIDIA A100 40GB',
12
- 'NVIDIA V100 16GB',
13
- 'NVIDIA P100 16GB',
14
- 'NVIDIA L4 24GB',
15
- 'NVIDIA T4 16GB',
16
- 'NVIDIA P4 8GB',
17
- )
18
- )
19
 
20
- # GPU Numbers
21
- gpu_numbers = st.slider('How many GPUs you would like to use?', 0, 8, 1)
22
 
23
- # CPU Cores
24
- cpu_numbers = st.slider('How many CPU Cores you would like to use?', 0, 208, 8)
25
 
26
- # Memory
27
- memory_size = st.slider('How many Memory you would like to use?', 0, 208, 8)
28
-
29
-
30
- # machines = [
31
- # "a3-highgpu-8g": {
32
- # "instance": "a3-highgpu-8g",
33
- # "gpu_numbers": 8,
34
- # "gpu_type": "NVIDIA H100 80GB",
35
- # "cpu_numbers": 208,
36
- # "memory": 1872,
37
- # "bundled_ssd": 6000,
38
- # "hourly_price_standard": 88.49,
39
- # "hourly_price_spot": 62.55,
40
- # },
41
- # "a2-ultragpu-1g": {
42
- # "instance": "a2-ultragpu-1g",
43
- # "gpu_numbers": 1,
44
- # "gpu_type": "NVIDIA A100 80GB",
45
- # "cpu_numbers": 12,
46
- # "memory": 170,
47
- # "bundled_ssd": 0,
48
- # "hourly_price_standard": 5.07,
49
- # "hourly_price_spot": 2.05,
50
- # },
51
- # "a2-ultragpu-2g": {
52
- # "instance": "a2-ultragpu-2g",
53
- # "gpu_numbers": 2,
54
- # "gpu_type": "NVIDIA A100 80GB",
55
- # "cpu_numbers": 24,
56
- # "memory": 340,
57
- # "bundled_ssd": 0,
58
- # "hourly_price_standard": 10.14,
59
- # "hourly_price_spot": 4.10,
60
- # },
61
- # "a2-ultragpu-4g": {
62
- # "instance": "a2-ultragpu-4g",
63
- # "gpu_numbers": 4,
64
- # "gpu_type": "NVIDIA A100 80GB",
65
- # "cpu_numbers": 48,
66
- # "memory": 680,
67
- # "bundled_ssd": 0,
68
- # "hourly_price_standard": 20.28,
69
- # "hourly_price_spot": 8.20,
70
- # },
71
- # "a2-ultragpu-8g": {
72
- # "instance": "a2-ultragpu-8g",
73
- # "gpu_numbers": 8,
74
- # "gpu_type": "NVIDIA A100 80GB",
75
- # "cpu_numbers": 96,
76
- # "memory": 1360,
77
- # "bundled_ssd": 0,
78
- # "hourly_price_standard": 40.55,
79
- # "hourly_price_spot": 16.39,
80
- # },
81
- # "a2-highgpu-1g": {
82
- # "instance": "a2-highgpu-1g",
83
- # "gpu_numbers": 1,
84
- # "gpu_type": "NVIDIA A100 40GB",
85
- # "cpu_numbers": 12,
86
- # "memory": 85,
87
- # "bundled_ssd": 0,
88
- # "hourly_price_standard": 3.67,
89
- # "hourly_price_spot": 1.47,
90
- # },
91
- # "a2-highgpu-2g": {
92
- # "instance": "a2-highgpu-2g",
93
- # "gpu_numbers": 2,
94
- # "gpu_type": "NVIDIA A100 40GB",
95
- # "cpu_numbers": 24,
96
- # "memory": 170,
97
- # "bundled_ssd": 0,
98
- # "hourly_price_standard": 7.35,
99
- # "hourly_price_spot": 2.94,
100
- # },
101
- # "a2-highgpu-4g": {
102
- # "instance": "a2-highgpu-4g",
103
- # "gpu_numbers": 4,
104
- # "gpu_type": "NVIDIA A100 40GB",
105
- # "cpu_numbers": 48,
106
- # "memory": 340,
107
- # "bundled_ssd": 0,
108
- # "hourly_price_standard": 14.69,
109
- # "hourly_price_spot": 5.88,
110
- # },
111
- # "a2-highgpu-8g": {
112
- # "instance": "a2-highgpu-8g",
113
- # "gpu_numbers": 8,
114
- # "gpu_type": "NVIDIA A100 40GB",
115
- # "cpu_numbers": 96,
116
- # "memory": 680,
117
- # "bundled_ssd": 0,
118
- # "hourly_price_standard": 29.39,
119
- # "hourly_price_spot": 11.76,
120
- # },
121
- # "a2-highgpu-16g": {
122
- # "instance": "a2-highgpu-16g",
123
- # "gpu_numbers": 16,
124
- # "gpu_type": "NVIDIA A100 40GB",
125
- # "cpu_numbers": 96,
126
- # "memory": 1360,
127
- # "bundled_ssd": 0,
128
- # "hourly_price_standard": 55.74,
129
- # "hourly_price_spot": 22.30,
130
- # },
131
- # ]
 
2
 
3
  st.title("GCP Resource Alloctor")
4
 
5
+ # # GPU Type
6
+ # gpu_type = st.selectbox(
7
+ # 'Which type of GPU you would like to use?',
8
+ # (
9
+ # 'NVIDIA H100 80GB',
10
+ # 'NVIDIA A100 80GB',
11
+ # 'NVIDIA A100 40GB',
12
+ # 'NVIDIA V100 16GB',
13
+ # 'NVIDIA P100 16GB',
14
+ # 'NVIDIA L4 24GB',
15
+ # 'NVIDIA T4 16GB',
16
+ # 'NVIDIA P4 8GB',
17
+ # )
18
+ # )
19
 
20
+ # # GPU Numbers
21
+ # gpu_numbers = st.slider('How many GPUs you would like to use?', 0, 8, 1)
22
 
23
+ # # CPU Cores
24
+ # cpu_numbers = st.slider('How many CPU Cores you would like to use?', 0, 208, 8)
25
 
26
+ # # Memory
27
+ # memory_size = st.slider('How many Memory you would like to use?', 0, 208, 8)