Apparate: Early-Exit Models for ML Latency and Throughput Optimization - Conclusion, References
3 Oct 2024
Apparate: A system that optimizes ML model inference by using adaptive early exits, reducing latency without sacrificing throughput or accuracy.
Apparate: Early-Exit Models for ML Latency and Throughput Optimization - Additional Related Work
3 Oct 2024
Apparate: A system that optimizes ML model inference by using adaptive early exits, reducing latency without sacrificing throughput or accuracy.
Apparate: Early-Exit Models for ML Latency and Throughput Optimization - Microbenchmarks
2 Oct 2024
Apparate: A system that optimizes ML model inference by using adaptive early exits, reducing latency without sacrificing throughput or accuracy.
Apparate: Early-Exit Models for ML Latency and Throughput Optimization - Comparisons
2 Oct 2024
Apparate: A system that optimizes ML model inference by using adaptive early exits, reducing latency without sacrificing throughput or accuracy.
Apparate: Early-Exit Models for ML Latency and Throughput Optimization - Overall Results
2 Oct 2024
Apparate: A system that optimizes ML model inference by using adaptive early exits, reducing latency without sacrificing throughput or accuracy.
Apparate: Early-Exit Models for ML Latency and Throughput Optimization - Evaluation and Methodology
2 Oct 2024
Apparate: A system that optimizes ML model inference by using adaptive early exits, reducing latency without sacrificing throughput or accuracy.
Apparate: Early-Exit Models for ML Latency and Throughput Optimization - Implementation
2 Oct 2024
Apparate: A system that optimizes ML model inference by using adaptive early exits, reducing latency without sacrificing throughput or accuracy.
Apparate: Early-Exit Models for ML Latency and Throughput Optimization - Latency-Focused Adjustments
2 Oct 2024
Apparate: A system that optimizes ML model inference by using adaptive early exits, reducing latency without sacrificing throughput or accuracy.
Apparate: Early-Exit Models for ML Latency and Throughput Optimization - Accurate Threshold Tuning
2 Oct 2024
Apparate: A system that optimizes ML model inference by using adaptive early exits, reducing latency without sacrificing throughput or accuracy.