Coded Sparse Matrix Multiplication
Authors: Sinong Wang, Jiashang Liu, Ness Shroff
ICML 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section, we present experimental results at Ohio Supercomputer Center (Center, 1987). We compare our proposed coding scheme against the following schemes: (i) uncoded scheme: the input matrices are divided uniformly across all workers and the master waits for all workers to send their results; (ii) sparse MDS code (Lee et al., 2017b)... Table 2. Timing Results for Different Sparse Matrix Multiplications (in sec) Data uncoded LT code sparse MDS code product code polynomial code sparse code square 6.81 3.91 6.42 6.11 18.44 2.17 |
| Researcher Affiliation | Academia | 1Department of ECE, The Ohio State University, Columbus, USA 2Departments of ECE and CSE, The Ohio State University, Columbus, USA. Correspondence to: Sinong Wang <wang.7691@osu.edu>. |
| Pseudocode | Yes | Algorithm 1 Sparse code (master node s protocol) |
| Open Source Code | No | The paper does not provide a link to source code or explicitly state that the code for the methodology is openly released. |
| Open Datasets | Yes | We also consider 8 sparse matrices from real data sets (Davis & Hu, 2011). |
| Dataset Splits | No | The paper refers to 'random Bernoulli square matrices' and 'real data sets' but does not explicitly provide training/validation/test dataset splits, percentages, or a detailed splitting methodology in the main text. |
| Hardware Specification | No | In this section, we present experimental results at Ohio Supercomputer Center (Center, 1987). |
| Software Dependencies | No | We implement all methods in python using MPI4py. |
| Experiment Setup | Yes | To simplify the simulation, we fix the number of workers N and randomly generate a coefficient matrix M RN mn under given degree distribution offline such that it can resist one straggler... We first generate two random Bernoulli sparse matrices with r = s = t = 150000 and 600000 nonzero elements. Figure. 5 reports the job completion time under m = n = 3, m = n = 4 and number of stragglers s = 2, 3, based on 20 experimental runs. |