Susan L. Graham mostly deals with Programming language, Parallel computing, Compiler, Operating system and Partitioned global address space. In her study, Susan L. Graham carries out multidisciplinary Programming language and Execution time research. Her Parallel computing research is multidisciplinary, incorporating perspectives in Interprocedural optimization, Loop optimization, Compiler correctness, Manifest expression and Partial redundancy elimination.
Her studies deal with areas such as Network monitoring, Enhanced Data Rates for GSM Evolution and Byte as well as Compiler. Her Operating system research integrates issues from Fault model and Embedded system. Susan L. Graham combines subjects such as Java, Model of computation and SPMD with her study of Partitioned global address space.
Her primary areas of investigation include Programming language, Compiler, Code generation, Parallel computing and Parsing. Her Programming language research is multidisciplinary, relying on both Artificial intelligence and Natural language processing. Her biological study spans a wide range of topics, including Debugger, Debugging, Session and Compiled language.
Her Parallel computing study typically links adjacent topics like Fortran. Her studies in SPMD integrate themes in fields like Model of computation and Global address space. Her research investigates the connection between Model of computation and topics such as Adaptive mesh refinement that intersect with problems in Unified Parallel C.
Susan L. Graham mainly focuses on Programming language, Java, Artificial intelligence, Natural language processing and Source code. Her Programming language study frequently draws connections between adjacent fields such as Operating system. When carried out as part of a general Java research project, her work on Real time Java is frequently linked to work in Task and Memory management, therefore connecting diverse disciplines of study.
Her study on Parsing is often connected to Fourth-generation programming language and Ontology language as part of broader study in Natural language processing. Her study in Source code is interdisciplinary in nature, drawing from both Software engineering, Usability and Macro. Her Partitioned global address space research includes elements of Message passing, Distributed memory, Shared memory and Parallel computing.
Her main research concerns Programming language, Operating system, Java, Supercomputer and Software engineering. Susan L. Graham regularly links together related areas like Distributed memory in her Programming language studies. The Operating system study combines topics in areas such as Message passing and Partitioned global address space, Unified Parallel C.
Her work carried out in the field of Java brings together such families of science as Software and Interface. Her Software engineering research is multidisciplinary, incorporating elements of Macro and Source code.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Efficient software-based fault isolation
Robert Wahbe;Steven Lucco;Thomas E. Anderson;Susan L. Graham.
symposium on operating systems principles (1994)
Gprof: A call graph execution profiler
Susan L. Graham;Peter B. Kessler;Marshall K. Mckusick.
compiler construction (1982)
Compiler transformations for high-performance computing
David F. Bacon;Susan L. Graham;Oliver J. Sharp.
ACM Computing Surveys (1994)
Titanium: a high-performance Java dialect
Katherine A. Yelick;Katherine A. Yelick;Luigi Semenzato;Luigi Semenzato;Geoff Pike;Geoff Pike;Carleton Miyamoto;Carleton Miyamoto.
Concurrency and Computation: Practice and Experience (1998)
A generalization of Dijkstra's calculus
Susan L. Graham.
ACM Transactions on Programming Languages and Systems (1989)
An Improved Context-Free Recognizer
Susan L. Graham;Michael Harrison;Walter L. Ruzzo.
ACM Transactions on Programming Languages and Systems (1980)
Managing Duplicated Code with Linked Editing
M. Toomim;A. Begel;S.L. Graham.
symposium on visual languages and human-centric computing (2004)
Productivity and performance using partitioned global address space languages
Katherine Yelick;Dan Bonachea;Wei-Yu Chen;Phillip Colella.
parallel symbolic computation (2007)
A Fast and Usually Linear Algorithm for Global Flow Analysis
Susan L. Graham;Mark Wegman.
Journal of the ACM (1976)
An execution profiler for modular programs
Susan L. Graham;Peter B. Kessler;Marshall K. McKusick.
Software - Practice and Experience (1983)
Profile was last updated on December 6th, 2021.
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