What is he best known for?
The fields of study he is best known for:
- Operating system
- Parallel computing
- Programming language
J. Ramanujam mostly deals with Parallel computing, Compiler, Optimizing compiler, Nested loop join and Automatic parallelization.
J. Ramanujam has researched Parallel computing in several fields, including Loop tiling, Stencil and Code generation.
His Loop tiling study combines topics in areas such as Loop fission, Loop nest optimization and General-purpose computing on graphics processing units.
His Compiler research is multidisciplinary, incorporating elements of Computer architecture, CUDA and Parallelism.
The concepts of his Optimizing compiler study are interwoven with issues in Memory architecture, Embedded system and Implementation.
The Nested loop join study combines topics in areas such as Deadlock, Shared memory and Affine transformation.
His most cited work include:
- A practical automatic polyhedral parallelizer and locality optimizer (678 citations)
- Dynamic management of scratch-pad memory space (266 citations)
- A compiler framework for optimization of affine loop nests for gpgpus (191 citations)
What are the main themes of his work throughout his whole career to date?
J. Ramanujam mainly investigates Parallel computing, Compiler, Algorithm, Computation and Optimizing compiler.
The study incorporates disciplines such as Code, Code generation and Loop nest optimization in addition to Parallel computing.
The various areas that J. Ramanujam examines in his Compiler study include Memory address, Multiprocessing, CUDA and Stencil.
His work deals with themes such as Tensor contraction, Loop tiling and Loop fusion, which intersect with Algorithm.
His Optimizing compiler research integrates issues from Program transformation, Program optimization and Embedded system.
His biological study spans a wide range of topics, including Scheduling and Affine transformation.
He most often published in these fields:
- Parallel computing (65.44%)
- Compiler (29.49%)
- Algorithm (16.13%)
What were the highlights of his more recent work (between 2013-2021)?
- Parallel computing (65.44%)
- Compiler (29.49%)
- Computation (14.75%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Parallel computing, Compiler, Computation, Theoretical computer science and Directed acyclic graph.
His Parallel computing study incorporates themes from Solver and Code.
His studies in Compiler integrate themes in fields like Affine transformation, Class, Stencil, Sequence and SIMD.
His Affine transformation course of study focuses on Loop optimization and Program optimization, Nested loop join and Transformation.
His study in Computation is interdisciplinary in nature, drawing from both Byte, Linear solver and Benchmark.
His research investigates the link between Theoretical computer science and topics such as Data access that cross with problems in CPU cache.
Between 2013 and 2021, his most popular works were:
- PLuTo: A Practical and Fully Automatic Polyhedral Program Optimization System (99 citations)
- Cross-Loop Optimization of Arithmetic Intensity for Finite Element Local Assembly (44 citations)
- A framework for enhancing data reuse via associative reordering (37 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Programming language
- Parallel computing
J. Ramanujam spends much of his time researching Parallel computing, Compiler, Affine transformation, Stencil and Computation.
In the field of Parallel computing, his study on Speedup overlaps with subjects such as Parametric array.
His Compiler study integrates concerns from other disciplines, such as Dependence analysis, Intrinsics and SIMD.
In his study, which falls under the umbrella issue of Affine transformation, Program optimization, Theoretical computer science, Nested loop join and Transformation is strongly linked to Loop optimization.
J. Ramanujam combines subjects such as Class, Parallel algorithm, Retiming and Associative property with his study of Stencil.
The Computation study combines topics in areas such as Spin glass, CUDA and Graphics processing unit.
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