Goals - Port LAPACK to Distributed-Memory Environments.

• Efficiency

  • Optimized compute and communication engines
  • Block-partitioned algorithms (Level 3 BLAS) utilize memory hierarchy and yield good node performance

• Reliability

  • Whenever possible, use LAPACK algorithms and error bounds.

• Scalability

  • As the problem size and number of processors grow
  • Replace LAPACK algorithm that did not scale; New ones into LAPACK

• Portability

  • Isolate machine dependencies to BLAS and the BLACS

• Flexibility

  • Modularity: Build rich set of linear algebra tools: BLAS, BLACS, PBLAS

• Ease-of-Use

  • Calling interface similar to LAPACK

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