Added Maxwell alternatives

Author: hariesramdhani

docs/working-with-hpc/gpu-on-maxwell.md

@@ -45,4 +45,4 @@ source ~/.bash_profile
 source ~/.bashrc
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-`--gres` (Generic Resource) parameter specifies the type and the number of GPUs required, so in this case I will be using NVIDIA A100 GPU and the number of GPUs that I will be using is 1, for the types and number of GPUs that you can use, please refer to the `GPU Code` and `Number of GPUs` column on the table respectively. For the `--partition` please refer to the `Partition` column 
+`--gres` (Generic Resource) parameter specifies the type and the number of GPUs required, so in this case I will be using NVIDIA A100 GPU and the number of GPUs that I will be using is 1, for the types and number of GPUs that you can use, please refer to the `GPU Code` and `Number of GPUs` column on the table respectively. For the `--partition` please refer to the `Partition` column.

docs/working-with-hpc/maxwell-alternatives.md

@@ -0,0 +1,58 @@
+---
+title: Maxwell Alternatives
+label: Maxwell Alternatives
+sidebar_position: 98
+---
+
+So Maxwell is down for a while now and you want to still work on your analyses, here are some alternatives (free compute power) that you can use:
+## [Google Colab](https://colab.research.google.com/)
+**Pros**:
+- Free access to GPUs (T4, P100) and TPUs
+- Jupyter notebook interface
+- You can connect to your Google Drive easily without additional libraries
+- Supports Python, R and Julia
+- Allows custom datasets, and pip/apt installs
+- Pro/Pro+ options offer longer sessions, more resources
+- Supports Gemini AI
+
+**Cons**:
+- Session timeout after 12 hrs (free), idle timeout ~90 mins, there's a hack for this but I will try to explain it on another post
+- Unstable availability of high-tier GPU
+- Your data will be gone once the session ends (So make sure to connect to your Google Drive)
+
+**Verdict**:
+- I love Google Colab for quick prototyping and testing my code for analysis, Gemini AI can be helpful sometimes too, the only thing that I hate about it is the timeout thing prevents you from running long process
+
+
+## [Kaggle Notebook](https://www.kaggle.com/code)
+**Pros**:
+- Free GPU (T4) and 16GB RAM, up to 30 hrs/week
+- Preloaded with many ML/DL libraries
+- Versioning (You can run your job and leave it be without the worry of having timeout like Google Colab)
+- Supports Python and R
+
+**Cons**:
+- GPU sessions limited to 9 hrs max
+- Fewer customizations than Colab
+- Require additional libraries to connect to external storage
+
+**Verdict**:
+- I usually go with Kaggle Notebook despite I like Google Colab UI better but Kaggle Notebook has everything you need most of the time
+
+## [Posit Cloud](https://posit.cloud/)
+**Pros**:
+- Designed specifically for R
+- Native RStudio interface — no setup needed
+- Great for RMarkdown, Shiny, Quarto, and teaching
+- Supports CRAN, Bioconductor, and GitHub packages
+- Persistent storage and auto-saving
+
+**Cons**:
+- No GPU/TPU access
+- Limited compute (1 GB RAM on free tier)
+- Session timeout after 1 hour (free)
+- 15 project-hours/month limit on free tier
+- Very slow for heavy data processing and sometimes it fails
+
+**Verdict**:
+- Only good for testing R packages on a small-sized dataset because of the fast installation of the packages, otherwise I barely use it