sgemm-gpu-kernel
OpenML dataset with id 42963
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22045632/sgemm-gpu-kernel.arff
Upload date: 28 May 2021
Dataset Characteristics
Number of features: 18 (numeric: 18, symbolic: 0 and in total binary: 0 )
Number of instances: 241,600
Number of instances with missing values: 0
Number of missing values: 0
Author: Enrique G. Paredes, Rafael Ballester-Ripoll Source: UCI - 2018 Please cite: Paper
SGEMM GPU kernel performance dataset
This data set measures the running time of a matrix-matrix product A x B = C, where all matrices have size 2048 x 2048, using a parameterizable SGEMM GPU kernel with 241600 possible parameter combinations. For each tested combination, 4 runs were performed and their results are reported as the 4 last columns. All times are measured in milliseconds*.
There are 14 parameter, the first 10 are ordinal and can only take up to 4 different powers of two values, and the 4 last variables are binary. Out of 1327104 total parameter combinations, only 241600 are feasible (due to various kernel constraints). This data set contains the results for all these feasible combinations.
The experiment was run on a desktop workstation running Ubuntu 16.04 Linux with an Intel Core i5 (3.5GHz), 16GB RAM, and a NVidia Geforce GTX 680 4GB GF580 GTX-1.5GB GPU. We use the 'gemm_fast' kernel from the automatic OpenCL kernel tuning library 'CLTune' ([Web Link]).
- Note: for this kind of data sets it is usually better to work with the logarithm of the running times (see e.g. Falch and Elster, 'Machine learning-based auto-tuning for enhanced performance portability of OpenCL applications', 2015).
Attribute information
Independent variables:
1-2. MWG, NWG: per-matrix 2D tiling at workgroup level: {16, 32, 64, 128} (integer)
3. KWG: inner dimension of 2D tiling at workgroup level: {16, 32} (integer)
4-5. MDIMC, NDIMC: local workgroup size: {8, 16, 32} (integer)
6-7. MDIMA, NDIMB: local memory shape: {8, 16, 32} (integer)
8. KWI: kernel loop unrolling factor: {2, 8} (integer)
9-10. VWM, VWN: per-matrix vector widths for loading and storing: {1, 2, 4, 8} (integer)
11-12. STRM, STRN: enable stride for accessing off-chip memory within a single thread: {0, 1} (categorical)
13-14. SA, SB: per-matrix manual caching of the 2D workgroup tile: {0, 1} (categorical)
Output:
15-18. Run1, Run2, Run3, Run4: performance times in milliseconds for 4 independent runs using the same parameters. They range between 13.25 and 3397.08.
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