Zobrazeno 1 - 10
of 122
pro vyhledávání: '"Broman, David"'
The choice of how to represent an abstract type can have a major impact on the performance of a program, yet mainstream compilers cannot perform optimizations at such a high level. When dealing with optimizations of data type representations, an impo
Externí odkaz:
http://arxiv.org/abs/2409.07950
How did humanity coax mathematics from the aether? We explore the Platonic view that mathematics can be discovered from its axioms - a game of conjecture and proof. We describe Minimo (Mathematics from Intrinsic Motivation): an agent that jointly lea
Externí odkaz:
http://arxiv.org/abs/2407.00695
Autor:
Yadav, Rohan, Bauer, Michael, Broman, David, Garland, Michael, Aiken, Alex, Kjolstad, Fredrik
Implicitly parallel task-based runtime systems often perform dynamic analysis to discover dependencies in and extract parallelism from sequential programs. Dependence analysis becomes expensive as task granularity drops below a threshold. Tracing tec
Externí odkaz:
http://arxiv.org/abs/2406.18111
Autor:
Opsahl-Ong, Krista, Ryan, Michael J, Purtell, Josh, Broman, David, Potts, Christopher, Zaharia, Matei, Khattab, Omar
Language Model Programs, i.e. sophisticated pipelines of modular language model (LM) calls, are increasingly advancing NLP tasks, but they require crafting prompts that are jointly effective for all modules. We study prompt optimization for LM progra
Externí odkaz:
http://arxiv.org/abs/2406.11695
The rapid growth in the size of deep learning models strains the capabilities of traditional dense computation paradigms. Leveraging sparse computation has become increasingly popular for training and deploying large-scale models, but existing deep l
Externí odkaz:
http://arxiv.org/abs/2405.16883
Complex cyber-physical systems interact in real-time and must consider both timing and uncertainty. Developing software for such systems is expensive and difficult, especially when modeling, inference, and real-time behavior must be developed from sc
Externí odkaz:
http://arxiv.org/abs/2311.06788
We propose the first method that determines the exact worst-case execution time (WCET) for implicit linear model predictive control (MPC). Such WCET bounds are imperative when MPC is used in real time to control safety-critical systems. The proposed
Externí odkaz:
http://arxiv.org/abs/2304.11576
Publikováno v:
Programming Languages and Systems. ESOP 2024. Lecture Notes in Computer Science, volume 14577
Universal probabilistic programming languages (PPLs) make it relatively easy to encode and automatically solve statistical inference problems. To solve inference problems, PPL implementations often apply Monte Carlo inference algorithms that rely on
Externí odkaz:
http://arxiv.org/abs/2302.13051
Publikováno v:
Programming Languages and Systems. ESOP 2023. Lecture Notes in Computer Science, volume 13990
Probabilistic Programming Languages (PPLs) allow users to encode statistical inference problems and automatically apply an inference algorithm to solve them. Popular inference algorithms for PPLs, such as sequential Monte Carlo (SMC) and Markov chain
Externí odkaz:
http://arxiv.org/abs/2301.11664