Design and Implement Architecture

Implement SPARC (Scalable Processing Architecture for Research Computing) cluster configurations and job scheduling

High-performance computing cluster setup for research workloads requiring massive parallelism and distributed scheduling.

• · SPARC cluster topology (node count, interconnect bandwidth, storage architecture)
• · Job specification (CPU count, memory, runtime, dependencies)
• · Scheduling policy (FIFO, priority queue, fairshare)

• · Deployed SPARC cluster with queue management
• · Job scheduler configuration (SLURM, PBS, or custom)
• · Resource allocation and load balancing verified

• · SLURM / PBS / SGE (job schedulers)
• · MPI libraries (OpenMPI, Intel MPI)
• · NFS or GPFS (shared storage)
• · Monitoring tools (Ganglia, Prometheus)

• · Physical SPARC hardware or VM cluster with network configured
• · Linux OS installed on all nodes
• · SSH key-based access configured between nodes

• · Job scheduler lock contention on metadata server (NFS performance degrades with many jobs)
• · Network congestion if interconnect underprovisioned relative to job count
• · Storage bottleneck (single NFS server limits I/O throughput)
• · Job isolation incomplete (noisy-neighbor jobs interfere with priorities)

• · SPARC architecture documentation from repository
• · Integration with standard HPC schedulers (SLURM, PBS, SGE)
• · MPI library support for distributed-memory applications