Ivan D. Baev

Approximation Algorithms for Data Placement Problems

We develop approximation algorithms for the problem of placing replicated data in arbitrary networks, where the nodes may both issue requests for data objects and have capacity for storing data objects so as to minimize the average data-access cost. We introduce the data placement problem to model this problem. We have a set of caches

An Experimental Study of Algorithms for Weighted Completion Time Scheduling

\mathcal{F}

Efficient Backtracking Instruction Schedulers

, a set of clients

Backtracking-Based Instruction Scheduling to Fill Branch Delay Slots

\mathcal{D}

Scheduling superblocks with bound-based branch trade-offs

, and a set of data objects

Techniques for Region-Based Register Allocation

\mathcal{O}

Lower bounds on precedence-constrained scheduling for parallel processors

. Each cache

Approximation algorithms for data placement in arbitrary networks

i

Algorithms for total weighted completion time scheduling

can store at most

Interprocedural register allocation for global variables

u_i