JeeWhan Choi

ACM SIGPLAN Symposium on Principles & Practice of Parallel Programming · 2010

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Whom JeeWhan Choi trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. R. Vuduc
  2. Eun-Jin Im
  3. Shubhabrata Sengupta
  4. J. Demmel
  5. K. Yelick
  6. Mark J. Harris
  7. Sunpyo Hong

Who trusts JeeWhan Choi overall

  1. Yao Zhang
  2. John Douglas Owens
  3. Weifeng Liu

Papers from JeeWhan Choi's perspective

Ordered by how strongly the researchers JeeWhan Choi trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Automatic performance tuning of sparse matrix kernels
  2. An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness (International Symposium on Computer Architecture)
  3. Sparsity: Optimization Framework for Sparse Matrix Kernels (The international journal of high performance computing applications)
  4. Scan primitives for GPU computing (GH '07)
  5. Sparse matrix solvers on the GPU: conjugate gradients and multigrid (ACM Transactions on Graphics)
  6. Automated empirical optimizations of software and the ATLAS project (Parallel Computing)
  7. OSKI: A library of automatically tuned sparse matrix kernels
  8. The potential of the cell processor for scientific computing
  9. Templates for the Solution of Algebraic Eigenvalue Problems (Software, environments, tools)
  10. An overview of the sparse basic linear algebra subprograms: The new standard from the BLAS technical forum

Their papers