Welcome @Gauravshree786
Hopefully we can help!
I’m going to link some resources below but I’m also curious about your goal? Do you want to assemble a transcriptome? For just one sample or many? Do you want to compare your samples to a known transcriptome? For differential expression or something else? If you are following a protocol, you can share that back here too for context!
I’m asking since there are alternative ways to “assemble” this kind of data that do not involve a full assembly and we can help to point you to methods for these.
QA
For assembly, the first item to review is how the reads are preprocessed. Assembly is very sensitive to read quality but also the content. Untrimmed adaptor can lead to processing issues and contaminated results.
Protocol
The second item to review is the sequencing depth. Higher coverage (deeper depth) doesn’t always add in more coverage information once resolved into an assembly. This means (most?) samples can be reduced to reduce the chance of overloading the algorithm.
If your species is known, you could try mapping your reads then reviewing the depth that way. You might notice where the pile ups are happening, and get an idea about how you could reduce depth while retaining overall coverage.
The help here applies to most assembly projects. Reduce the coverage then try tuning the tool parameters.
Transcriptomics
Finally, if you are curious about how psudo-assembly works, we have some polished tutorials and example workflows in our 
Galaxy Training Network (GTN) Tutorials!
I’ll also add in this in case you are new to Galaxy! The QA module may be interesting!
Then we have production quality workflows in the 
IWC Workflow Library. These can be imported and used intact or you can modify them to suit your goals.
Let’s start there! And I was just guessing about your error being a memory failure. If it was something else, or if you are not sure, you are welcome to share back a link to your history and we can help to troubleshoot what is specifically going wrong. 