High Performance Computing for Precision Medicine
About This Course
Learners should be able to
1) Evaluate and explain the runtime complexity of algorithms used in analysing data for precision medicine
2) Describe the architecture of high-performance systems and relate it to the latencies in processing data
3) Evaluate data processing workflows and identify bottlenecks using profiling methods
4) Explain the different models of parallel computing
5)Evaluate and identify suitable applications that utilize parallel computing for accelerating workflows
6) Parallelize a high-throughput workflow and optimize the bottlenecks where necessary
7) Containerize applications and binaries for reproducible computing in a shared high-performance system environment
What You'll Learn
Entry Requirements
Applicants must have a Bachelor’s degree and may be required to show relevant work experience. Applicants with other qualifications and experience may be considered on a case by case basis, subject to approval by the school. Familiarity with Linux environment