A2BCD: Asynchronous Acceleration with Optimal Complexity
Authors: Robert Hannah, Fei Feng, Wotao Yin
ICLR 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | To investigate the performance of A2BCD, we solve the ridge regression problem. ... We use the datasets w1a (47272 samples, 300 features), wxa ... and aloi ... We use 40 threads on two 2.5GHz 10-core Intel Xeon E5-2670v2 processors. ... In Table 5, we plot the sub-optimality vs. time for decreasing values of λ, which corresponds to increasingly large condition numbers κ. |
| Researcher Affiliation | Academia | Robert Hannah , Fei Feng , Wotao Yin Department of Mathematics University of California, Los Angeles 520 Portola Plaza, Los Angeles, CA 90095, USA |
| Pseudocode | Yes | Algorithm 1 Shared-memory implementation of A2BCD |
| Open Source Code | No | The paper mentions implementation details ('implemented in a multi-threaded fashion using C++11 and GNU Scientific Library') but does not provide an explicit statement or link indicating that the source code for their method is publicly available. |
| Open Datasets | Yes | We use the datasets w1a (47272 samples, 300 features), wxa which combines the data from from w1a to w8a (293201 samples, 300 features), and aloi (108000 samples, 128 features) from LIBSVM Chang & Lin (2011). |
| Dataset Splits | No | The paper mentions the datasets and their sizes but does not specify the training, validation, or test split percentages or sample counts for reproduction. |
| Hardware Specification | Yes | We use 40 threads on two 2.5GHz 10-core Intel Xeon E5-2670v2 processors. |
| Software Dependencies | Yes | The algorithm is implemented in a multi-threaded fashion using C++11 and GNU Scientific Library. |
| Experiment Setup | Yes | The parameters for each algorithm are tuned to give the fastest performance, so that a fair comparison is possible. ... Through simple tuning though, we found that ψ = 0.25 resulted in good performance. |