Publications

@article{WOS:000560566100004,

title = {Sparse Matrix-Vector Multiplication on a Map-Reduce Many-Core 

 Accelerator},

author = {Voichita Dragomir and Gheorghe M. Stefan},

issn = {1453-8245},

year  = {2020},

date = {2020-01-01},

journal = {ROMANIAN JOURNAL OF INFORMATION SCIENCE AND TECHNOLOGY},

volume = {23},

number = {3},

pages = {262-273},

publisher = {EDITURA ACAD ROMANE},

address = {CALEA 13 SEPTEMBRIE NR 13, SECTOR 5, BUCURESTI 050711, ROMANIA},

abstract = {Our proposal for accelerating the computation of Sparse Matrix Vector 

 Multiplication is a Map-Reduce Accelerator as part of a heterogenous 

 computer. We prove that both, structured and unstructured sparse 

 matrices are efficiently multiplied with a dense vector approach using a 

 parallel accelerator structured as a linear array of cells loop 

 connected, through a log-depth reduction network, with a controller. The 

 specific algorithms are presented and their implementation is compared 

 with the of-the-shelf solutions. The main advantages of our 

 architectural proposal, compared with the GeForce GTX 280 GPU which is 

 implemented in the same technological node, are: (1) it provides the 

 means to use 5 divided by 12x more computation out of the peak 

 computational power, (2) it performs the computation with 2.5 x less 

 energy.},

keywords = {sparse matrix; matrix-vector multiplication; unstructured sparse matrix;   structured sparse matrix; heterogenous computing},

pubstate = {published},

tppubtype = {article}

}