Search Results for author:
Found 8 papers, 3 papers with code
VEXIR2Vec: An Architecture-Neutral Embedding Framework for Binary Similarity
We show results on several standard projects and on real-world vulnerabilities.
The Next 700 ML-Enabled Compiler Optimizations
There is a growing interest in enhancing compiler optimizations with ML models, yet interactions between compilers and ML frameworks remain challenging.
POSET-RL: Phase ordering for Optimizing Size and Execution Time using Reinforcement Learning
We observe that the proposed model based on ODG outperforms the current Oz sequence both in terms of size and execution time by 6. 19% and 11. 99% in SPEC 2017 benchmarks, on an average.
RL4ReAl: Reinforcement Learning for Register Allocation
We aim to automate decades of research and experience in register allocation, leveraging machine learning.
Hierarchical Reinforcement Learning
Multi-agent Reinforcement Learning
+2
PolyDL: Polyhedral Optimizations for Creation of High Performance DL primitives
However, given the constant emergence of new DNN architectures, creating hand optimized code is expensive, slow and is not scalable.
PolyScientist: Automatic Loop Transformations Combined with Microkernels for Optimization of Deep Learning Primitives
In this paper, we develop a hybrid solution to the development of deep learning kernels that achieves the best of both worlds: the expert coded microkernels are utilized for the innermost loops of kernels and we use the advanced polyhedral technology to automatically tune the outer loops for performance.
LLOV: A Fast Static Data-Race Checker for OpenMP Programs
In the era of Exascale computing, writing efficient parallel programs is indispensable and at the same time, writing sound parallel programs is very difficult.
Programming Languages Logic in Computer Science Software Engineering D.2; D.3
IR2Vec: LLVM IR based Scalable Program Embeddings
As our infrastructure is based on the Intermediate Representation (IR) of the source code, obtained embeddings are both language and machine independent.
