A Communication- and Memory-Aware Model for Load Balancing Tasks
arxiv(2024)
摘要
While load balancing in distributed-memory computing has been well-studied,
we present an innovative approach to this problem: a unified, reduced-order
model that combines three key components to describe "work" in a distributed
system: computation, communication, and memory. Our model enables an optimizer
to explore complex tradeoffs in task placement, such as increased parallelism
at the expense of data replication, which increases memory usage. We propose a
fully distributed, heuristic-based load balancing optimization algorithm, and
demonstrate that it quickly finds close-to-optimal solutions. We formalize the
complex optimization problem as a mixed-integer linear program, and compare it
to our strategy. Finally, we show that when applied to an electromagnetics
code, our approach obtains up to 2.3x speedups for the imbalanced execution.
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