Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: FPGA vs. GPU for sparse matrix vector multiply
Floating-point sparse matrix-vector multiply for FPGAs
ecient sparse matrix - vector multiplication on cuda .
Automatic Selection of Sparse Matrix Representation on GPUs
Performance portable GPU code generation for matrix multiplication
Automatic tuning matrix multiplication performance on graphics hardware
Benchmarking GPUs to tune dense linear algebra
GPU-Accelerated Parallel Sparse LU Factorization Method for Fast Circuit Analysis
Efficient multithreaded untransposed, transposed or symmetric sparse matrix-vector multiplication with the Recursive Sparse Blocks format
GPU-Accelerated Bulk Computation of the Eigenvalue Problem for Many Small Real Non-symmetric Matrices
Fast Cholesky factorization on GPUs for batch and native modes in MAGMA
A Comparison of the Performance of SaP::GPU and Intel's Math Kernel Library (MKL) for Solving Dense Banded Linear Systems
CUDA Based Fast Implementation of Very Large Matrix Computation
Anatomy of high-performance matrix multiplication
Generalized Cannon's algorithm for parallel matrix multiplication
Optimizing the Matrix Multiplication Using Strassen and Winograd Algorithms with Limited Recursions on Many-Core
Communication-optimal parallel 2.5D matrix multiplication and LU factorization algorithms
batched matrix computations on hardware accelerators based on gpus .
GPU Versus FPGA for High Productivity Computing
Efficient Structured Multifrontal Factorization for General Large Sparse Matrices
A Fast Batched Cholesky Factorization on a GPU
Value-added uses for crude glycerol--a byproduct of biodiesel production
FPGA-based real-time optical-flow system
Is Faster R-CNN Doing Well for Pedestrian Detection?
A New Notion of Compositionality for Concurrent Program Proofs (Invited Talk)
Quality of life in elderly patients following coronary artery bypass grafting