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libusb3380-0t64
USB3380 abstraction layer for libusb
The USB 3380 is a PCI Express Gen 2 to USB 3.0 SuperSpeed Peripheral
Controller. It features one PCI Express Gen 2 x1 port and one USB 3.0
SuperSpeed client port. The USB 3380 provides a matching bandwidth at 5 GT/s
between the PCI Express Gen 2 bus and the USB 3.0 SuperSpeed bus.
libjheaps-java
Java library with various heap implementations
This library contains various heap implementations written in Java.
A heap is a priority queue data type which contains elements with keys
(duplicate keys are permitted) from a totally-ordered universe.
The library is easy to use, its data structures have a well defined interface,
it is fast and well documented, and the heaps are written in a similar way as
in the JDK.
libslepc64-complex3.19
Scalable Library for Eigenvalue Problem Computations (64-bit)
SLEPc is a software library for the solution of large scale sparse eigenvalue
problems on parallel computers. It is an extension of PETSc and can be used
for either standard or generalized eigenproblems, with real or complex
arithmetic. It can also be used for computing a partial SVD of a large,
sparse, rectangular matrix.
libslepc-real3.19
Scalable Library for Eigenvalue Problem Computations
SLEPc is a software library for the solution of large scale sparse eigenvalue
problems on parallel computers. It is an extension of PETSc and can be used
for either standard or generalized eigenproblems, with real or complex
arithmetic. It can also be used for computing a partial SVD of a large,
sparse, rectangular matrix.
libfilezilla39
build high-performing platform-independent programs (runtime lib)
Free, open source C++ library, offering some basic functionality to build
high-performing, platform-independent programs. Some of the highlights include:
libslepc-complex3.19
Scalable Library for Eigenvalue Problem Computations
SLEPc is a software library for the solution of large scale sparse eigenvalue
problems on parallel computers. It is an extension of PETSc and can be used
for either standard or generalized eigenproblems, with real or complex
arithmetic. It can also be used for computing a partial SVD of a large,
sparse, rectangular matrix.