OpenCV + Java + Linux
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Sunday, July 26, 2009
Saturday, July 25, 2009
WEB4J. Because simple is beautiful.
The important things about WEB4J are :
- it's an open source, full-stack Java web app framework
- it let's you build a browser front-end to a relational database
- it's small, and has a philosophy of deep simplicity and minimalism
- it lets you put SQL in plain .sql text files
- it lets you implement forms with plain old HTML
- it can significantly boost your productivity compared to other tools
- it allows package-by-feature, where closely related items are placed in the same directory
- it protects you from common hacks
- it has no reliance on javascript
- it has no custom annotations
- it has no custom .xml files (only web.xml is used)
- it has no object-relational mapping
- it can be used with any relational database that has a JDBC driver
- it lets your Model Objects be immutable
- it lets your Model Objects be responsible for their own validation (as they should be)
- it lets your Model Objects avoid the Java Beans anti-pattern
- it has nice building block classes
- it uses a minimal toolset
- it doesn't take you long to learn (and you don't need to buy a big fat book)
- it uses convention over configuration in several important ways
- it makes your application classes simple, and easy to maintain
- it requires minimal configuration
- it doesn't impose thread-safety constraints on your classes
- it lets multilingual apps have almost the same style as a single language app
- it lets your apps assist in their own translation
- it lets you place translations in the database
- it lets you avoid ResourceBundle and its defects
- it allows apps to share a fake system clock with the framework, so they remain in sync
- it starts up quickly
faint - The Face Annotation Interface
This project is a flexible Java framework for face detection and face recognition technologies, that is based on different plugin and filter types. A suitable graphical interface can be used to set up pipelines for detection and recognition by combining these plugins and filters. Moreover an integrated photo browser allows users to apply the face detection and recognition process on personal images.
nVidia CUDA
NVIDIA® CUDA™ technology leverages the massively parallel processing power of NVIDIA GPUs. The CUDA architecture is a revolutionary parallel computing architecture that delivers the performance of NVIDIA’s world-renowned graphics processor technology to general purpose GPU Computing. Applications that run on the CUDA architecture can take advantage of an installed base of over one hundred million CUDA-enabled GPUs in desktop and notebook computers, professional workstations, and supercomputer clusters.
With the CUDA architecture and tools, developers are achieving dramatic speedups in fields such as medical imaging and natural resource exploration, and creating breakthrough applications in areas such as image recognition and real-time HD video playback and encoding. CUDA enables this unprecedented performance via standard APIs such as the soon to be released OpenCL™ and DirectX® Compute, and high level programming languages such as C/C++, Fortran, Java, Python, and the Microsoft .NET Framework.
The CUDA Developer SDK provides examples with source code to help you get started with CUDA. Examples include:
- Parallel bitonic sort
- Matrix multiplication
- Matrix transpose
- Performance profiling using timers
- Parallel prefix sum (scan) of large arrays
- Image convolution
- 1D DWT using Haar wavelet
- OpenGL and Direct3D graphics interoperation examples
- CUDA BLAS and FFT library usage examples
- CPU-GPU C- and C++-code integration
- Binomial Option Pricing
- Black-Scholes Option Pricing
- Monte-Carlo Option Pricing
- Parallel Mersenne Twister (random number generation)
- Parallel Histogram
- Image Denoising
- Sobel Edge Detection Filter
Sunday, July 19, 2009
Thursday, July 9, 2009
Tweaking hard disk on Linux
hdparm -Tt /dev/hda
/dev/hda:
Timing buffer-cache reads: 128 MB in 1.34 seconds =95.52 MB/sec
Timing buffered disk reads: 64 MB in 17.86 seconds = 3.58 MB/sec
hdparm /dev/hda
/dev/hda:
multcount = 0 (off)
I/O support = 0 (default 16-bit)
unmaskirq = 0 (off)
using_dma = 0 (off)
keepsettings = 0 (off)
nowerr = 0 (off)
readonly = 0 (off)
readahead = 8 (on)
geometry = 1870/255/63, sectors = 30043440, start = 0
- multcount: Short for multiple sector count. This controls how many sectors are fetched from the disk in a single I/O interrupt. Almost all modern IDE drives support this. The man page claims: when this feature is enabled, it typically reduces operating system overhead for disk I/O by 30-50%. On many systems, it also provides increased data throughput of anywhere from 5% to 50%.
- I/O support: This is a big one. This flag controls how data is passed from the PCI bus to the controller. Almost all modern controller chipsets support mode 3, or 32-bit mode w/sync. Some even support 32-bit async. Turning this on will almost certainly double your throughput (see below.)
- unmaskirq: Turning this on will allow Linux to unmask other interrupts while processing a disk interrupt. What does that mean? It lets Linux attend to other interrupt-related tasks (i.e., network traffic) while waiting for your disk to return with the data it asked for. It should improve overall system response time, but be warned: Not all hardware configurations will be able to handle it. See the manpage.
- using_dma: DMA can be a tricky business. If you can get your controller and drive using a DMA mode, do it. But I have seen more than one machine hang while playing with this option.
hdparm -X66 -d1 -u1 -m16 -c3 /dev/hda:
setting 32-bit I/O support flag to 3
setting multcount to 16
setting unmaskirq to 1 (on)
setting using_dma to 1 (on)
setting xfermode to 66 (UltraDMA mode2)
multcount = 16 (on)
I/O support = 3 (32-bit w/sync)
unmaskirq = 1 (on)
using_dma = 1 (on)
hdparm -tT /dev/hda
/dev/hda:
Timing buffer-cache reads: 128 MB in 1.43 seconds = 89.51 MB/sec
Timing buffered disk reads: 64 MB in 3.18 seconds = 20.13 MB/sec
Monday, July 6, 2009
Saturday, July 4, 2009
An Eclipse 3.5 Galileo is here !
An Eclipse Galileo 3.5
What's new in the latest version of the open source multipurpose IDE and application platform
Galileo is the simultaneous release of 33 major Eclipse projects. The Eclipse Foundation states that the Galileo release train consists of 33 projects. However, some are subprojects that are rolled up into projects, and not all projects are highlighted in the Eclipse Foundation's marketing push. Regardless, Galileo represents the largest single release of new technology to date.
The important thing to remember about Galileo in particular and Eclipse release trains in general is that even though it's a simultaneous release, it doesn't mean these projects are unified. Each project is a separate open source project, operating with its own project leadership, its own committers, and its own development plan. The release train concept is designed to provide a transparent and predictable development cycle.
There are two main ways to get Galileo. The first — and recommended — way is to just grab a package relevant to you. The other way to get Galileo is to use an update site.
Go to the Eclipse Galileo Packages site. The packages site contains nine pre-bundled versions of Galileo specific for your needs.
To get Galileo using an update site, download the Eclipse V3.5 SDK. Once this is done, you can launch Eclipse and access the software-update mechanism via Help > Software Updates (see Figure 2). Enter the proper Galileo update site information, if it isn't already available as the Galileo Discovery Site. Once you are connected to the Galileo update site, you should see the list of available features that are part of the Galileo release train. It's as simple as that. Once you're connected, you can simply choose what features to install into your Eclipse.
Figure 2. Software updates
The Eclipse ecosystem is a large and sometimes intimidating place. About 100 projects are being overseen by the Eclipse Foundation, and the Galileo release only represents a snapshot of that. The Galileo release train showcases Eclipse technology and helps adopters integrate Eclipse technology into their products. For more information about the Galileo projects, see the links below.
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