Results - GDCC

Board of experts of 3th Edition of the Global Data Compression Competition (2023)

Prof. Wen Gao, Peking University, China.

Boya Chair Professor and Director of Faculty of Information and Engineering Sciences at Peking University (China). Served as Vice president of National Natural Science Foundation China (NSFC) and president of China Computer Federation (CCF). Deputy Director of China National Standardization Technical Committees. He works in the areas of multimedia and computer vision, including video coding, video analysis, multimedia retrieval, face recognition, and multimodal interface.

Professor Shmuel Tomi Klein, Bar Ilan University, Israel.

Professor at Bar Ilan University (Israel). His research interests are Lossless Data Compression, Information Storage and Retrieval, Text Algorithms, and Computational Linguistics.

Prof. Michael W. Marcellin, University of Arizona, USA.

Regents Professor, Faculty Fellow, and Honors Professor at University of Arizona (United States of America). His research interests are Digital Communication and Data Storage Systems, Data Compression, and Signal Processing.

Prof. Dmitry Vatolin, Lomonosov Moscow State University, Russia.

Head of ML/DL video processing, compression, and quality research lab at Lomonosov Moscow State University (Russia). His research interests are video and image processing and compression, and multimedia data processing.

Professor Gonzalo Navarro, Universidad de Chile, Chile.

Professor at University of Chile (Chile). His research interests are Design and analysis of algorithms and data structures, Compressed data structures, Text databases, Information retrieval, and Metric databases.

ORGANIZERS OF 4TH EDITION OF THE GLOBAL DATA COMPRESSION COMPETITION

Professor Serra Sagristà, Universitat Autònoma de Barcelona, Spain.

Joan Serra-Sagristà received the Ph.D. degree in computer science from Universitat Autònoma Barcelona (UAB), Spain, in 1999. He is currently a Full Professor at Department of Information and Communications Engineering, UAB. He is the Head of the Group on Interactive Coding of Images (GICI) since 2003 and the Head of the Department since 2018. From September 1997 to December 1998, he was at University of Bonn, Germany, funded by German Academic Exchange Service (DAAD) and by Catalan Savings Bank "La Caixa". His current research interests focus on source coding / data compression, with special attention to data coding for remote sensing applications. He serves or has served as Senior Area Editor for IEEE Trans. on Image Processing, as Associate Editor for IEEE Trans. on Geoscience and Remote Sensing, IEEE Trans. on Image Processing, SPIE Journal of Electronic Imaging, among others, and as Program Committee co-chair for IEEE Data Compression Conference, among others. He has co-authored over 150 publications. He was the recipient of the Spanish Intensification Young Investigator Award in 2006.

Associate Professor Bartrina Rapesta, Universitat Autònoma de Barcelona, Spain

Joan Bartrina-Rapesta received the B.Sc., B.E., M.S., and Ph.D. degrees in computer science from the Universitat Autònoma de Barcelona (UAB), Spain, in 2002, 2004, 2006, and 2009, respectively. He obtains his M.S. and Ph.D. degree with highest honors from UAB. He was awarded with a doctoral fellowship from UAB. He participates as a reviewer for magazines and symposiums, has co-authored numerous papers in journals and conferences, and has guided Ph.D. students. From 2012 to present, he holds an associate professor position with the Department of Information and Communications Engineering in the UAB. His research interests include a wide range of image coding topics, computing, and transmission.

PhD Student Fernández Mellado, Universitat Autònoma de Barcelona, Spain.

Xavier Fernández-Mellado received the B.E. and M.S. degrees in computer science and telecomunications from the Universitat Autònoma de Barcelona (UAB), Spain, in 2023 and 2024, respectively. He is currently a PhD candidate in the Group of Interactive Coding of Images (GICI) at UAB, focusing on advanced research in image compression. He has contributed as a technical engineer at the Institut d'Estudis Espacials de Catalunya (IEEC) and is the co-author of two conference papers on innovative developments in the field.

PhD Student Quintas Torra, Universitat Autònoma de Barcelona, Spain.

Pau Quintas-Torra received the B.E. and M.S. degrees in computer science from the Universitat Autònoma de Barcelona (UAB), Spain, in 2023 and 2024, respectively. He is currently a PhD candidate in the Group of Interactive Coding of Images (GICI) at UAB, focusing on advanced research in image compression. He has contributed as a technical engineer at the Institut d'Estudis Espacials de Catalunya (IEEC) and is the co-author of two conference papers on innovative developments in the field.

4th Edition Leaderboards

The leaderboard tables below contain results for contest submissions and reference compressors.

List of tests (see the rules for a complete description):

• Task 1: Qualitative Data Lossless Recompression
• Task 2: Quantitative Data Lossless Recompression
• Task 3: JPEG Lossless Recompression
• Task 4: Fast Row-Column Exchange

Task 1

Task 1
Task 2
Task 3
Task 4

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Rapid
High Compression Ratio
Fast Row-Column Exchange

Private

Table Notes

We placed compressors that fell just outside a given speed category, as well as compressors that were too slow for the high-compression-ratio (HCR) category, at the bottom of the corresponding table.
The suffix NS stands for “not a student”, meaning the competitor is ineligible for monetary awards in the student category.
The suffix GP means the compressor won the 20,000 EUR Grand Prize in the rapid-compression category of Test 4.
The suffix 1–2 indicates the compressor won the 5,000 EUR First-to-Second-Place Gap Prize in the respective category.
Regarding inclusion of compressors in slower categories: A compressor from a faster category appears in a slower category’s leaderboard if it scores among the top 3 of the latter and if the competition committee believes it’s more than just a minor variation of the submission by the same author for the slower category. In particular, “alpha” and “beta” were deemed sufficiently different, so both appeared in the Test 3 HCR category. On the other hand, the committee decided that compressors in the pairs {“gamma”, “delta”} and {“epsilon”, “zeta”} were merely “light” and “heavy” versions of the same compressor. In cases where the leaderboard includes such a variation, other submissions from the original top three retain their places and associated prizes; thus, two entries may share the same place in the final top three.
All compressors that are present in the table were tested under Windows 10 x64 OS and with the test hardware as described in Test Hardware.
Reference compressors for Test 4 were tested so that for every 8K subblock the entire 64K block was decoded to extract that subblock, so in effect the entire dataset was decoded 8 times (see more detailed for Zstd and brotli).
Sample (demo) datasets: Test 1, Test 2, Test 3, Test 4. The password for all sample-data 7z archives is 9568. The sizes of the sample (training) datasets are, respectively, 300,000,000 bytes, 500,004,864 bytes, 500,000,000 bytes, and 500,039,680 bytes.
Private datasets: Test 1, Test 2, Test 3, Test 4. The sizes of the private datasets are, respectively, 1,000,000,000 bytes, 1,000,911,424 bytes, 1,000,000,000 bytes, and 1,000,013,824 bytes.

Charts for leaderboards

General notes

The line joining the markers for different compressors on the scatter plot shows the Pareto frontier. That is, for each such compressor, no other analyzed programs in that category achieve better results for both the selected time and compression parameters.
The names of submitted compressors appear in boldface.

Task 1, Rapid

Task 1, Rapid
Task 1, High Compression Ratio
Task 2, Rapid
Task 2, High Compression Ratio
Task 3, Rapid
Task 3, High Compression Ratio

Full time

Full time
Compression time
Decompression time

c_full_size

c_full_size
c_full_size, megabytes
Compression ratio
Compression ratio, bits per byte

Compressor Ranking

Participating Compressors

Name	Submission Date	Task	Competition category	Status

Reference Compressors

Name	Task	Competition category	Status

4th Edition of the Global Data Compression Competition