157 citations · 177 across the 20 of their papers we have counts for
5 papers · 1 filter
Optimizing Tensor Computation Graphs with Equality Saturation and Monte Carlo Tree Search
Jakob Hartmann, Guoliang He, Eiko Yoneki
The real-world effectiveness of deep neural networks often depends on their latency, thereby necessitating optimization techniques that can reduce a model's inference time while pr…
Navigating in High-Dimensional Search Space: A Hierarchical Bayesian Optimization Approach
Wenxuan Li, Taiyi Wang, Eiko Yoneki
Optimizing black-box functions in high-dimensional search spaces has been known to be challenging for traditional Bayesian Optimization (BO). In this paper, we introduce HiBO, a no…
Learned Graph Rewriting with Equality Saturation: A New Paradigm in Relational Query Rewrite and Beyond
George-Octavian Bărbulescu, Taiyi Wang, Zak Singh +1
Query rewrite systems perform graph substitutions using rewrite rules to generate optimal SQL query plans. Rewriting logical and physical relational query plans is proven to be an…
IA2: Leveraging Instance-Aware Index Advisor with Reinforcement Learning for Diverse Workloads
Taiyi Wang, Eiko Yoneki
This study introduces the Instance-Aware Index Advisor (IA2), a novel deep reinforcement learning (DRL)-based approach for optimizing index selection in databases facing large acti…
SIP: Autotuning GPU Native Schedules via Stochastic Instruction Perturbation
Guoliang He, Eiko Yoneki
Large language models (LLMs) have become a significant workload since their appearance. However, they are also computationally expensive as they have billions of parameters and are…