Algorithmic skeletons: structured management of parallel computation
Algorithmic skeletons: structured management of parallel computation
Safe fusion of functional expressions
LFP '92 Proceedings of the 1992 ACM conference on LISP and functional programming
FPCA '93 Proceedings of the conference on Functional programming languages and computer architecture
Deforestation: Transforming Programs to Eliminate Trees
ESOP '88 Proceedings of the 2nd European Symposium on Programming
An Accumulative Parallel Skeleton for All
ESOP '02 Proceedings of the 11th European Symposium on Programming Languages and Systems
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
Systematic Efficient Parallelization of Scan and Other List Homomorphisms
Euro-Par '96 Proceedings of the Second International Euro-Par Conference on Parallel Processing-Volume II
ICCD '02 Proceedings of the 2002 IEEE International Conference on Computer Design: VLSI in Computers and Processors (ICCD'02)
Single Assignment C: efficient support for high-level array operations in a functional setting
Journal of Functional Programming
Brook for GPUs: stream computing on graphics hardware
ACM SIGGRAPH 2004 Papers
GPGPU: general purpose computation on graphics hardware
ACM SIGGRAPH 2004 Course Notes
A new parallel skeleton for general accumulative computations
International Journal of Parallel Programming
A library of constructive skeletons for sequential style of parallel programming
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
Merging compositions of array skeletons in SAC
Parallel Computing - Algorithmic skeletons
QUAFF: efficient C++ design for parallel skeletons
Parallel Computing - Algorithmic skeletons
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Merge: a programming model for heterogeneous multi-core systems
Proceedings of the 13th international conference on Architectural support for programming languages and operating systems
BlockLib: a skeleton library for cell broadband engine
Proceedings of the 1st international workshop on Multicore software engineering
Mars: a MapReduce framework on graphics processors
Proceedings of the 17th international conference on Parallel architectures and compilation techniques
OpenMP to GPGPU: a compiler framework for automatic translation and optimization
Proceedings of the 14th ACM SIGPLAN symposium on Principles and practice of parallel programming
Flexible skeletal programming with eskel
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Domain-specific optimization strategy for skeleton programs
Euro-Par'07 Proceedings of the 13th international Euro-Par conference on Parallel Processing
SkePU: a multi-backend skeleton programming library for multi-GPU systems
Proceedings of the fourth international workshop on High-level parallel programming and applications
Accelerating Haskell array codes with multicore GPUs
Proceedings of the sixth workshop on Declarative aspects of multicore programming
Auto-tuning SkePU: a multi-backend skeleton programming framework for multi-GPU systems
Proceedings of the 4th International Workshop on Multicore Software Engineering
Introducing 'Bones': a parallelizing source-to-source compiler based on algorithmic skeletons
Proceedings of the 5th Annual Workshop on General Purpose Processing with Graphics Processing Units
Kernel Weaver: Automatically Fusing Database Primitives for Efficient GPU Computation
MICRO-45 Proceedings of the 2012 45th Annual IEEE/ACM International Symposium on Microarchitecture
Optimising purely functional GPU programs
Proceedings of the 18th ACM SIGPLAN international conference on Functional programming
| Hi-index | 0.00 |
Although today's graphics processing units (GPUs) have high performance and general-purpose computing on GPUs (GPGPU) is actively studied, developing GPGPU applications remains difficult for two reasons. First, both parallelization and optimization of GPGPU applications is necessary to achieve high performance. Second, the suitability of the target application for GPGPU must be determined, because whether an application performs well with GPGPU heavily depends on its inherent properties, which are not obvious from the source code. To overcome these difficulties, we developed a skeletal parallel programming framework for rapid GPGPU application developments. It enables programmers to easily write GPGPU applications and rapidly test them because it generates programs for both GPUs and CPUs from the same source code. It also provides an optimization mechanism based on fusion transformation. Its effectiveness was confirmed experimentally.