Current Competitions

Subnet 1 Apex competitions registry

Matrix Compression

The first competition - Matrix Compression - explores how small neural activations - both forward and backward - can be compressed while still retaining all their original information. Reducing activation size enables faster data transfer across the internet, a crucial step toward making distributed training more efficient, as it’s often constrained by network bandwidth. The top-performing algorithms from this competition will be integrated to enhance training on subnet 9 IOTA.

Evaluation

Miners aim to optimize the following:

  • Compression Ratio - How small the compressed solution is on disk versus the starting matrix.

  • Time - How fast the compression/decompression algorithm runs.

To surpass the current winner of the competition, a miner must earn a raw score of at least 1% higher than the current top score. If there is no current winner, then a miner must earn a raw score of at least 1% higher than the baseline score.

  • The score_to_beat is displayed in the Apex CLI dashboard, under competition information.

Raw score is calculated by:

raw_score = 1 * (30 - task_time) + 1000 * similarity + 1000000 * compression_ratio
  • Where task_time includes both compression and decompression.

  • Similarity is calculated by cosine_similarity * norm_similarity.

  • Compression ratio is calculated by original_size / compressed_file_size.

This raw score is then normalized with a sigmoid normalization function:

normalized_score = 1 / (1 + np.exp(-0.003 * (raw_score / 1000 - 2000)))
  • Where a normalized score of 0.5 correlates to a raw score of 2,000,000.

For Miners

View the matrix compression baseline miner solutionarrow-up-right provided as an example.

View the matrix compression general miner solutionarrow-up-right template.

Test your solution with the provided samples in this R2 bucket: https://pub-77097c3387c340de9ff1bd5e5b443d8d.r2.devarrow-up-right. Files are listed in manifest.csv

  • First, download manifest.csv from the R2 bucket to access all sample file names.

  • You will then be able to access all sample files with their given file names.

Then, continue to the Apex CLI guidearrow-up-right to submit a solution.

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