T
Todd C. Mowry
Researcher at Carnegie Mellon University
Publications - 117
Citations - 9806
Todd C. Mowry is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Cache & Compiler. The author has an hindex of 49, co-authored 113 publications receiving 9137 citations. Previous affiliations of Todd C. Mowry include University of Toronto & Stanford University.
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Proceedings ArticleDOI
Design and evaluation of a compiler algorithm for prefetching
TL;DR: This paper proposes a compiler algorithm to insert prefetch instructions into code that operates on dense matrices, and shows that this algorithm significantly improves the execution speed of the benchmark programs-some of the programs improve by as much as a factor of two.
Proceedings ArticleDOI
Ambit: in-memory accelerator for bulk bitwise operations using commodity DRAM technology
Vivek Seshadri,Donghyuk Lee,Thomas Mullins,Hasan Hassan,Amirali Boroumand,Jeremie S. Kim,Michael Kozuch,Onur Mutlu,Phillip B. Gibbons,Todd C. Mowry +9 more
TL;DR: Ambit is proposed, an Accelerator-in-Memory for bulk bitwise operations that largely exploits existing DRAM structure, and hence incurs low cost on top of commodity DRAM designs (1% of DRAM chip area).
Proceedings ArticleDOI
Compiler-based prefetching for recursive data structures
Chi-Keung Luk,Todd C. Mowry +1 more
TL;DR: It is demonstrated that compiler-inserted prefetching can significantly improve the execution speed of pointer-based codes---as much as 45% for the applications the authors study and can improve performance by as much as twofold.
Proceedings ArticleDOI
A scalable approach to thread-level speculation
TL;DR: This paper proposes and evaluates a design for supporting TLS that seamlessly scales to any machine size because it is a straightforward extension of writeback invalidation-based cache coherence (which itself scales both up and down).
Proceedings ArticleDOI
The potential for using thread-level data speculation to facilitate automatic parallelization
J.G. Steffan,Todd C. Mowry +1 more
TL;DR: The potential for using thread-level data speculation (TLDS) to overcome this limitation by allowing the compiler to view parallelization solely as a cost/benefit tradeoff rather than something which is likely to violate program correctness is explored.