5 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.AR2024
LLM-Aided Compilation for Tensor Accelerators
Charles Hong, Sahil Bhatia, Altan Haan +4
Hardware accelerators, in particular accelerators for tensor processing, have many potential application domains. However, they currently lack the software infrastructure to suppor…
cs.PL2024★ 5 cited
Verified Code Transpilation with LLMs
Sahil Bhatia, Jie Qiu, Niranjan Hasabnis +2
Domain-specific languages (DSLs) are integral to various software workflows. Such languages offer domain-specific optimizations and abstractions that improve code readability and m…
cs.PL2023
Code Transpilation for Hardware Accelerators
Yuto Nishida, Sahil Bhatia, Shadaj Laddad +3
DSLs and hardware accelerators have proven to be very effective in optimizing computationally expensive workloads. In this paper, we propose a solution to the challenge of manually…