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CellBuzz: The Sony-Toshiba-IBM Cell Broadband Engine is a heterogeneous multicore architecture that consists of a traditional microprocessor (PPE) with eight SIMD co-processing units (SPEs) integrated on-chip. This repository contains Cell B.E. optimized libraries and software for FFT, MPEG, compression, and encryption.
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The Sony-Toshiba-IBM Cell Broadband Engine is a heterogeneous multicore architecture that consists of a traditional microprocessor (PPE) with eight SIMD co-processing units (SPEs) integrated on-chip. This repository contains Cell Broadband Engine Processor optimized libraries and software, developed by David A. Bader and his research group, for a number of libraries for FFT, MPEG, compression, and encryption. This project also includes patches to accelerate R on the Cell Broadband Engine processor.
fft: Fast Fourier Transform (FFT) is an efficient algorithm that is used for computing Discrete Fourier Transform. FFT is of primary importance and a fundamental kernel in many computationally intensive scientific applications such as computer tomography, data filtering and fluid dynamics. Another important application area of FFTs is in spectral analysis of speech, sonar, radar, seismic and vibration detection. FFTs are also used in digital filtering, signal decomposition, and in solution of partial differential equations. The performance of these applications rely heavily on the availability of a fast routine for Fourier Transforms. There are several algorithmic variants of the FFTs that have been well studied for parallel processors and vector architectures. In our design we utilize the naive Cooley-Tukey radix-2 Decimate in Frequency algorithm. The algorithm runs in logN stages and each stage requires O(N) computation, where N is the input size.
"FFTC: Fastest Fourier Transform for the IBM Cell Broadband Engine," David A. Bader and Virat Agarwal, The 14th Annual IEEE International Conference on High Performance Computing (HiPC 2007), S. Aluru et al., (eds.), Springer-Verlag LNCS 4873, 172-184, Goa, India, December 18-21, 2007.
"Computing Discrete Transforms on the Cell Broadband Engine," David A. Bader, Virat Agarwal, and Seunghwa Kang, Parallel Computing, 35(3):119-137, 2009.
jpeg2000: JPEG2000 is the latest still image coding standard from the JPEG committee, which adopts new algorithms such as embedded block coding with optimized truncation (EBCOT) and discrete wavelet transform (DWT). These algorithms enable superior coding performance over JPEG and support various new features at the cost of the increased computational complexity. The Sony-Toshiba-IBM cell broadband engine (or the Cell/B.E.) is a heterogeneous multicore architecture with SIMD accelerators. In this work, we optimize the computationally intensive algorithmic kernels of JPEG2000 for the Cell/B.E. and also introduce a novel data decomposition scheme to achieve high performance with low programming complexity. We compare the Cell/B.E.‘s performance to the performance of the Intel Pentium IV 3.2 GHz processor. The Cell/B.E. demonstrates 3.2 times higher performance for lossless encoding and 2.7 times higher performance for lossy encoding. For the DWT, the Cell/B.E. outperforms the Pentium IV processor by 9.1 times for the lossless case and 15 times for the lossy case. We also provide the experimental results on one IBM QS20 blade with two Cell/B.E. chips and the performance comparison with the existing JPEG2000 encoder for the Cell/B.E.
minigzip: Minigzip for Sony-Toshiba-IBM Cell Broadband Engine (or Cell processor) is a file compression/decompression utility similar to gzip (http://www.gzip.org). Minigzip, provided here is programmed using zlib library optimized for Cell Processor. Zlib, a data compression/decompression library, was originally written by Jean-loup Gailly and Mark Adler (http://www.zlib.net). While zlib is heavily optimized for sequential execution environment, additional effort is required to exploit Cell processor's unique architecture.
mpeg2: While the Cell/B.E. processor is designed with multimedia applications in mind, there are currently no open-source, optimized implementations of such applications available. In this paper, we present the design and implementation behind the creation of an optimized MPEG-2 software decoder for this unique parallel architecture, and demonstrate its performance through an experimental study. This is the first parallelization of an MPEG-2 decoder for a commodity heterogeneous multicore processor such as the IBM Cell/B.E. While Drake et al. have recently parallelized MPEG-2 using Streamlt for a streaming architecture, our algorithm is quite different and is the first to address the new challenges related to the optimization and tuning of a multicore algorithm with DMA transfers and local store memory. Our design and efficient implementation target the architectural features provided by the heterogeneous multicore processor. We give an experimental study on Sony PlayStation 3 and IBM QS20 dual-Cell Blade platforms. For instance, using 16 SPEs on the IBM QS20, our decoder runs 3.088 times faster than a 3.2 GHz Intel Xeon and achieves a speedup of over 10.545 compared with a PPE-only implementation. Our source code is freely- available through SourceForge under the CellBuzz project.
rc5: RC5 is a block cipher that was originally designed by Ronald Rivest paper. We have implemented and optimized the RC5 encryption/decryption library for the Sony-Toshiba-IBM Cell Broadband Engine. RC5 is widely used in message encryption, digital signatures, stream encryption, internet e-commerce, file encryption, electronic cash, etc. This library has been implemented by Virat Agarwal and David A. Bader.
zlib: The Sony–Toshiba–IBM Cell Broadband Engine (Cell/B.E.) is a heterogeneous multicore architecture that consists of a traditional microprocessor (PPE) with eight SIMD co-processing units (SPEs) integrated on-chip. While the Cell/B.E. processor is architected for multimedia applications with regular processing requirements, we are interested in its performance on problems with non-uniform memory access patterns. In this article, we present two case studies to illustrate the design and implementation of parallel combinatorial algorithms on Cell/B.E.: we discuss list ranking, a fundamental kernel for graph problems, and zlib, a data compression and decompression library. List ranking is a particularly challenging problem to parallelize on current cache-based and distributed memory architectures due to its low computational intensity and irregular memory access patterns. To tolerate memory latency on the Cell/B.E. processor, we decompose work into several independent tasks and coordinate computation using the novel idea of Software-Managed threads (SM-Threads). We apply this generic SPE work-partitioning technique to efficiently implement list ranking, and demonstrate substantial speedup in comparison to traditional cache-based microprocessors. For instance, on a 3.2 GHz IBM QS20 Cell/B.E. blade, for a random linked list of 1 million nodes, we achieve an overall speedup of 8.34 over a PPE-only implementation. Our second case study, zlib, is a data compression/decompression library that is extensively used in both scientific as well as general purpose computing. The core kernels in the zlib library are the LZ77 longest subsequence matching algorithm and Huffman data encoding. We design efficient parallel algorithms for these combinatorial kernels, and exploit concurrency at multiple levels on the Cell/B.E. processor. We also present a Cell/B.E. optimized implementation of gzip, a popular file-compression application based on the zlib library. For our Cell/B.E. implementation of gzip, we achieve an average speedup of 2.9 in compression over current workstations.