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05/26/2023
Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time
Large language models(LLMs) have sparked a new wave of exciting AI appli...
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07/21/2022
The trade-offs of model size in large recommendation models : A 10000 × compressed criteo-tb DLRM model (100 GB parameters to mere 10MB)
Embedding tables dominate industrial-scale recommendation model sizes, u...
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07/21/2022
Efficient model compression with Random Operation Access Specific Tile (ROAST) hashing
Advancements in deep learning are often associated with increasing model...
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08/04/2021
Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000× Compression and 2.7× Faster Inference
Deep learning for recommendation data is the one of the most pervasive a...
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02/26/2021
Beyond Convolutions: A Novel Deep Learning Approach for Raw Seismic Data Ingestion
Traditional seismic processing workflows (SPW) are expensive, requiring ...
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02/24/2021
Semantically Constrained Memory Allocation (SCMA) for Embedding in Efficient Recommendation Systems
Deep learning-based models are utilized to achieve state-of-the-art perf...
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02/24/2021
Density Sketches for Sampling and Estimation
We introduce Density sketches (DS): a succinct online summary of the dat...
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01/02/2021
Smart Car Features using Embedded Systems and IoT
There has been a tremendous rise in technological advances in the field ...
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10/29/2020