What is SkeTo?
SkeTo (Skeletons in Tokyo) is a constructive parallel skeleton library written in C++ with MPI intended for distributed environments such as PC clusters. SkeTo provides data parallel skeletons for lists (distributed onedimensional arrays), matrices (distributed twodimensional arrays), and trees (distributed binary trees). SkeTo enables users to write parallel programs as if they were sequential, since the distribution, gathering, and parallel computation of data are concealed within constructors of data types or definitions of parallel skeletons. This is the results of the research of the "SkeTo Project".
The latest version of SkeTo (version 1.5) does not include tree skeletons due to the delay of the restructuring process of the entire code. They will be available in the near future. To use tree skeletons, please download the older version (version 0.21).
SkeTo is named after the Japanese word "Suketto", whose meaning is helper or supporter, in the hope that SkeTo library will help programmers easily develop efficient parallel programs.
NEWS
 SkeTo version 1.50 prereleased [February 2013]
 SkeTo version 1.50 (pre) is now available. New features of this version are variablelength list skeletons, such as filter and concatmap, and a new fusion mechanism for them.
 SkeTo version 1.1 released [December 2010]
 SkeTo version 1.1 is now available. New features of this version are matrix skeletons with fusion optimization, data serialization that supports lists/matrices of variablesized data (e.g., a list of strings), and experimental support for lambda expressions in C++0x.
 Presentations at HLPP 2010 [September 2010]
 Hu made an invited talk titled ''Calculational Parallel Programming'', and Matsuzaki presented an experience of using the SkeTo library through the implementation of the BiCGStab method.
SkeTo Project
"SkeTo Project" is a research project working on skeletal parallelism (or algorithmic skeletons).
We are studying parallel skeletons based on the constructive algorithmics. The main contributions of our project are as follows:
 Parallel Skeletons for Several Data Structures: The constructive algorithms provides a general handling of various data structures. Based on this, we are studying parallel skeletons for lists, matrices, and trees.
 Optimization Mechanism for Skeletal Programs: A program with many skeletons may lead undesirable overheads. We are studying an optimization mechanism of the skeletal programs, based on the program transformation techniques.
This project has been partially supported by:
 HPC Systems Inc.,
 PRESTO program by Japan Science and Technology Agency (JST),
 GrantinAid for Scientific Research (B), No. 17300005, Japan Society for the Promotion of Science, and
 GrantinAid for Scientific Research (C), No. 20500029, Japan Society for the Promotion of Science.
Results
We have proposed several fundamental parallel skeletons for data structures lists, matrices, and trees based on the BMF (BirdMeertens Formalism), which provides a concise interface of skeletons, and shown their efficient implementations. We have also formalized and proposed the optimization mechanism by the fusion transformation over parallel skeletons on lists.
We implemented our ideas as a parallel skeleton library. The current version of our parallel skeleton library includes several data parallel skeletons for lists, matrices, and trees. The optimization mechanism is now implemented by the C++template technique called expression templates. Our parallel skeleton library is available from the Download page.
Members
SkeTo is a joint project of The University of Tokyo, The University of ElectroCommunications, National Institute of Informatics, and Kochi University of Technology in Japan.
Current Members
 Kento EMOTO (The University of Tokyo)
 Zhenjiang HU (National Institute of Informatics)
 Hideya IWASAKI (The University of ElectroCommunications)
 Yu LIU (National Institute of Informatics)
 Kiminori MATSUZAKI (Kochi University of Technology)
 Shigeyuki SATO (The University of ElectroCommunications)
Old Members
Yoshiki AKASHI, Kousuke ARIMA, Yu ISHIDO, Kazuhiko KAKEHI, Yuki KARASAWA, Kazutoshi KARIYA, Shunji KINOSHITA, Yoshiaki NOMURA, Noriyuki OHKAWA, Haruto TANNO, Masato TAKEICHI
Publications
2013

Kento Emoto,
Kiminori Matsuzaki
An Automatic Fusion Mechanism for VariableLength List Skeletons in SkeTo.
METR 201304, Department of Mathematical Engineering and Information Physics, The University of Tokyo, 2013.)
2010

Kiminori Matsuzaki,
Kento Emoto:
Lessons from Implementing the BiCGStab Method with SkeTo Library
Fourth International Workshop on Highlevel Parallel Programming and Applications (HLPP 1010), pp.1524, 2010. 
Kiminori Matsuzaki,
Kento Emoto:
Implementing FusionEquipped Parallel Skeletons by Expression Templates
Implementation and Application of Functional Languages: 21st International Symposium, IFL 2009, Revised Selected Papers, Lecture Notes in Computer Science 6041, Springer, pp.7289, 2010.
2009

Shigeyuki Sato,
Hideya Iwasaki:
A Skeletal Parallel Framework with Fusion Optimizer for GPGPU Programming
7th Asian Symposium on Programming Languages and Systems (APLAS 2009), Lecture Notes in Computer Science 5904, Springer, pp.7994, 2009. 
Kiminori Matsuzaki,
Kento Emoto:
Implementing FusionEquipped Parallel Skeletons by Expression Templates
Draft Proceedings of the 21st International Symposium on Implementation and Application of Functional Languages (IFL 2009), Technical Report: SHUTRCS2009091, Seton Hall University, pp.100115, 2009.
(Revised version appears as above.) 
Yuki Karasawa,
Hideya Iwasaki:
A Parallel Skeleton Library for Multicore Clusters
38th International Conference on Parallel Processing (ICPP 2009), pp.8491, 2009. 
Haruto Tanno,
Hideya Iwasaki:
Parallel Skeletons for Variablelength Lists in SkeTo Skeleton Library
15th International EuroPar Conference (EuroPar 2009), Lecture Notes in Computer Science 5704, Springer, pp.666677, 2009.
2008

Yuki Karasawa,
Hideya Iwasaki:
Parallel Skeletons for Sparse Matrices in SkeTo Skeleton Library
IPSJ Transactions on Programming, Vol.49, No.SIG 3 (PRO 36), pp.115, 2008.
(PDF file of this paper is available also from the IMP page.)
2007

Kento Emoto,
Zhenjiang Hu,
Kazuhiko Kakehi,
Masato Takeichi:
A Compositional Framework for Developing Parallel Programs on Two Dimensional Arrays
International Journal of Parallel Programming, Vol.35, No.6, pp.615658, 2007. 
Kento Emoto,
Kiminori Matsuzaki,
Zhenjiang Hu,
Masato Takeichi:
DomainSpecific Optimization Strategy for Skeleton Programs
13th International EuroPar Conference (EuroPar 2007), Lecture Notes in Computer Science 4641, Springer, pp.705714, 2009. 
Kiminori Matsuzaki:
Efficient Implementation of Tree Accumulations on DistributedMemory Parallel Computers
Fourth International Workshop on Practical Aspects of Highlevel Parallel Programming (PAPP 2007), part of The International Conference on Computational Science (ICCS 2007), Lecture Notes in Computer Science 4488, Springer, pp.609616, 2007. 
Kazuhiko Kakehi,
Kiminori Matsuzaki,
Kento Emoto:
Efficient Parallel Tree Reductions on Distributed Memory Environments
Fourth International Workshop on Practical Aspects of Highlevel Parallel Programming (PAPP 2007), part of The International Conference on Computational Science (ICCS 2007), Lecture Notes in Computer Science 4488, Springer, pp.601608, 2007.
2006

Kiminori Matsuzaki,
Zhenjiang Hu,
Masato Takeichi:
Parallel Skeletons for Manipulating General Trees
Parallel Computing, Vol.32, No.78, pp.590603, 2006.

Kento Emoto,
Kiminori Matsuzaki,
Zhenjiang Hu,
Masato Takeichi:
Surrounding Theorem: Developing Parallel Programs for MatrixConvolutions
12th International EuroPar Conference (EuroPar 2006), Lecture Notes in Computer Science 4128, Springer, pp.605614, 2006. 
Kiminori Matsuzaki,
Zhenjiang Hu,
Masato Takeichi:
Towards Automatic Parallelization of Tree Reductions in Dynamic Programming
18th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2006), pp.3948, 2006.

Kiminori Matsuzaki,
Kento Emoto,
Hideya Iwasaki,
Zhenjiang Hu:
A Library of Constructive Skeletons for Sequential Style of Parallel Programming (Invited Paper)
First International Conference on Scalable Information Systems (InfoScale 2006), 2006.
2005

Kiminori Matsuzaki,
Zhenjiang Hu,
Kazuhiko Kakehi,
Masato Takeichi:
Systematic Derivation of Tree Contraction Algorithms
Parallel Processing Letters, Vol.15, No.3, pp.321336, 2005.
2004

Hideya Iwasaki,
Zhenjiang Hu:
A New Parallel Skeleton for General Accumulative Computations
International Journal of Parallel Programming, Vol.32, No.5, pp.389414, 2004.

Kiminori Matsuzaki,
Kazuhiko Kakehi,
Hideya Iwasaki,
Zhenjiang Hu,
Yoshiki Akashi:
A FusionEmbedded Skeleton Library
10th International EuroPar Conference (EuroPar 2004), Lecture Notes in Computer Science 3149, Springer, pp.644653, 2004.

Kiminori Matsuzaki,
Kazuhiko Kakehi,
Zhenjiang Hu,
Masato Takeichi:
Systematic Derivation of Tree Contraction Algorithms
4th International Workshop on Constructive Methods for Parallel Programming (CMPP 2004), Technical Report of Westfalische wilhelmsuniveersitat munster, pp.109123.
(Revised version appears as above.)
2003

Kazuhiko Kakehi,
Zhenjiang Hu,
Masato Takeichi:
List Homomorphism with Accumulation
4th International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2003), pp.250259, 2003.

Kiminori Matsuzaki,
Zhenjiang Hu,
Masato Takeichi:
Parallelization with Tree Skeletons
9th International EuroPar Conference (EuroPar 2003), Lecture Notes in Computer Science 2790, Springer, pp.789798, 2003.
(An extended version appears as Mathematical Engineering Technical Report METR 200321, Department of Mathematical Engineering and Information Physics, The University of Tokyo, 2003.)