Person:
Prieto Matías, Manuel

First Name

Manuel

Last Name

Prieto Matías

URI

https://hdl.handle.net/20.500.14352/78600

Affiliation

Universidad Complutense de Madrid

Faculty / Institute

Informática

Department

Arquitectura de Computadores y Automática

Area

Arquitectura y Tecnología de Computadores

Identifiers

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Search Results

Now showing 1 - 10 of 20

2-D wavelet transform enhancement on general-purpose microprocessors: memory hierarchy and SIMD parallelism exploitation
(High performance computing - HIPC 2002, proceedings, 2002) Chaver Martínez, Daniel Ángel; Tenllado Van Der Reijden, Christian Tomás; Piñuel Moreno, Luis; Prieto Matías, Manuel; Tirado Fernández, José Francisco
This paper addresses the implementation of a 2-D Discrete Wavelet Transform on general-purpose microprocessors, focusing on both memory hierarchy and SIMD parallelization issues. Both topics are somewhat related, since SIMD extensions are only useful if the memory hierarchy is efficiently exploited. In this work, locality has been significantly improved by means of a novel approach called pipelined computation, which complements previous techniques based on loop tiling and non-linear layouts. As experimental platforms we have employed a Pentium-III (P-III) and a Pentium-4 (P-4) microprocessor. However, our SIMD-oriented tuning has been exclusively performed at source code level. Basically, we have reordered some loops and introduced some modifications that allow automatic vectorization. Taking into account the abstraction level at which the optimizations are carried out, the speedups obtained on the investigated platforms are quite satisfactory, even though further improvement can be obtained by dropping the level of abstraction (compiler intrinsics or assembly code).
Robust motion estimation on a low-power multi-core DSP
(Eurasip journal on advances in signal processing, 2013) Igual Peña, Francisco Daniel; Botella Juan, Guillermo; García Sánchez, Carlos; Prieto Matías, Manuel; Tirado Fernández, José Francisco
Medical imaging has become an absolutely essential diagnostic tool for clinical practices; at present, pathologies can be detected with an earliness never before known. Its use has not only been relegated to the field of radiology but also, increasingly, to computer-based imaging processes prior to surgery. Motion analysis, in particular, plays an important role in analyzing activities or behaviors of live objects in medicine. This short paper presents several low-cost hardware implementation approaches for the new generation of tablets and/or smartphones for estimating motion compensation and segmentation in medical images. These systems have been optimized for breast cancer diagnosis using magnetic resonance imaging technology with several advantages over traditional X-ray mammography, for example, obtaining patient information during a short period. This paper also addresses the challenge of offering a medical tool that runs on widespread portable devices, both on tablets and/or smartphones to aid in patient diagnostics.
Offset printing plate quality sensor on a low-cost processor
(Sensors, 2013) Poljak, Jelena; Botella Juan, Guillermo; García Sánchez, Carlos; Poljacek, Sanja Mahovic; Prieto Matías, Manuel; Tirado Fernández, José Francisco
The aim of this work is to develop a microprocessor-based sensor that measures the quality of the offset printing plate through the introduction of different image analysis applications. The main features of the presented system are the low cost, the low amount of power consumption, its modularity and easy integration with other industrial modules for printing plates, and its robustness against noise environments. For the sake of clarity, a viability analysis of previous software is presented through different strategies, based on dynamic histogram and Hough transform. This paper provides performance and scalability data compared with existing costly commercial devices. Furthermore, a general overview of quality control possibilities for printing plates is presented and could be useful to a system where such controls are regularly conducted.
LFOC: A Lightweight Fairness-Oriented Cache Clustering Policy for Commodity Multicores
(2019) García García, Adrián; Sáez Alcaide, Juan Carlos; Castro Rodríguez, Fernando; Prieto Matías, Manuel
Multicore processors constitute the main architecture choice for modern computing systems in different market segments. Despite their benefits, the contention that naturally appears when multiple applications compete for the use of shared resources among cores, such as the last-level cache (LLC), may lead to substantial performance degradation. This may have a negative impact on key system aspects such as throughput and fairness. Assigning the various applications in the workload to separate LLC partitions with possibly different sizes, has been proven effective to mitigate shared-resource contention effects. In this article we propose LFOC, a clustering-based cache partitioning scheme that strives to deliver fairness while providing acceptable system throughput. LFOC leverages the Intel Cache Allocation Technology (CAT), which enables the system software to divide the LLC into different partitions. To accomplish its goals, LFOC tries to mimic the behavior of the optimal cache-clustering solution, which we could approximate by means of a simulator in different scenarios. To this end, LFOC effectively identifies streaming aggressor programs and cache sensitive applications, which are then assigned to separate cache partitions. We implemented LFOC in the Linux kernel and evaluated it on a real system featuring an Intel Skylake processor, where we compare its effectiveness to that of two state-of-the-art policies that optimize fairness and throughput, respectively. Our experimental analysis reveals that LFOC is able to bring a higher reduction in unfairness by leveraging a lightweight algorithm suitable for adoption in a real OS.
Formation of stellar inner discs and rings in spiral galaxies through minor mergers
(Fourth Science Meeting with the GTC, 2013) Eliche Moral, María del Carmen; González García, A. C.; Balcells, M.; Aguerri, J.A.L.; Gallego Maestro, Jesús; Zamorano Calvo, Jaime; Prieto Matías, Manuel
Recent observations show that inner disks and rings (IDs and IRs) are not preferentially found in barred galaxies, pointing to the relevance of formation mechanisms different to the traditional bar-origin scenario. Nevertheless, the role of minor mergers in the formation of these inner components (ICs), while often invoked, is still poorly understood. We have investigated the capability of minor mergers to trigger the formation of IDs and IRs in spiral galaxies through collisionless N-body simulations. Our models prove that minor mergers are an efficient mechanism to form rotationally-supported stellar ICs in spirals, neither requiring strong dissipation nor noticeable bars, and suggest that their role in the formation of ICs must have been much more complex than just bar triggering.
A low cost matching motion estimation sensor based on the NIOS II microprocessor.
(Sensors, 2012) González, Diego; Botella Juan, Guillermo; Meyer Baese, Uwe; García Sánchez, Carlos; Sanz, Concepción; Prieto Matías, Manuel; Tirado Fernández, José Francisco
Medical imaging has become an absolutely essential diagnostic tool for clinical practices; at present, pathologies can be detected with an earliness never before known. Its use has not only been relegated to the field of radiology but also, increasingly, to computer-based imaging processes prior to surgery. Motion analysis, in particular, plays an important role in analyzing activities or behaviors of live objects in medicine. This short paper presents several low-cost hardware implementation approaches for the new generation of tablets and/or smartphones for estimating motion compensation and segmentation in medical images. These systems have been optimized for breast cancer diagnosis using magnetic resonance imaging technology with several advantages over traditional X-ray mammography, for example, obtaining patient information during a short period. This paper also addresses the challenge of offering a medical tool that runs on widespread portable devices, both on tablets and/or smartphones to aid in patient diagnostics.
Fast-Coding Robust Motion Estimation Model in a GPU
(2015) García Sánchez, Carlos; Botella Juan, Guillermo; Sande, Francisco de; Prieto Matías, Manuel
Nowadays vision systems are used with countless purposes. Moreover, the motion estimation is a discipline that allow to extract relevant information as pattern segmentation, 3D structure or tracking objects. However, the real-time requirements in most applications has limited its consolidation, considering the adoption of high performance systems to meet response times. With the emergence of so-called highly parallel devices known as accelerators this gap has narrowed. Two extreme endpoints in the spectrum of most common accelerators are Field Programmable Gate Array (FPGA) and Graphics Processing Systems (GPU), which usually offer higher performance rates than general propose processors. Moreover, the use of GPUs as accelerators involves the efficient exploitation of any parallelism in the target application. This task is not easy because performance rates are affected by many aspects that programmers should overcome. In this paper, we evaluate OpenACC standard, a programming model with directives which favors porting any code to a GPU in the context of motion estimation application. The results confirm that this programming paradigm is suitable for this image processing applications achieving a very satisfactory acceleration in convolution based problems as in the well-known Lucas & Kanade method.
Customized Nios II multi-cycle instructions to accelerate block-matching techniques
(SPIE Proceedings, 2015) González, Diego; Botella Juan, Guillermo; García Sánchez, Carlos; Meyer Bäse, Anke; Meyer Bäse, Uwe; Prieto Matías, Manuel
This study focuses on accelerating the optimization of motion estimation algorithms, which are widely used in video coding standards, by using both the paradigm based on Altera Custom Instructions as well as the efficient combination of SDRAM and On-Chip memory of Nios II processor. Firstly, a complete code profiling is carried out before the optimization in order to detect time leaking affecting the motion compensation algorithms. Then, a multi-cycle Custom Instruction which will be added to the specific embedded design is implemented. The approach deployed is based on optimizing SOC performance by using an efficient combination of On-Chip memory and SDRAM with regards to the reset vector, exception vector, stack, heap, read/write data (.rwdata), read only data (.rodata), and program text (.text) in the design. Furthermore, this approach aims to enhance the said algorithms by incorporating Custom Instructions in the Nios II ISA. Finally, the efficient combination of both methods is then developed to build the final embedded system. The present contribution thus facilitates motion coding for low-cost Soft-Core microprocessors, particularly the RISC architecture of Nios II implemented in FPGA. It enables us to construct an SOC which processes 50×50 @ 180 fps.
Big-PERCIVAL: Exploring the Native Use of 64-Bit Posit Arithmetic in Scientific Computing
(IEEE Transactions on Computers, 2024) Mallasén Quintana, David; Del Barrio García, Alberto Antonio; Prieto Matías, Manuel
The accuracy requirements in many scientific computing workloads result in the use of double-precision floating-point arithmetic in the execution kernels. Nevertheless, emerging real-number representations, such as posit arithmetic, show promise in delivering even higher accuracy in such computations. In this work, we explore the native use of 64-bit posits in a series of numerical benchmarks and compare their timing performance, accuracy and hardware cost to IEEE 754 doubles. In addition, we also study the conjugate gradient method for numerically solving systems of linear equations in real-world applications. For this, we extend the PERCIVAL RISC-V core and the Xposit custom RISC-V extension with posit64 and quire operations. Results show that posit64 can obtain up to 4 orders of magnitude lower mean square error than doubles. This leads to a reduction in the number of iterations required for convergence in some iterative solvers. However, leveraging the quire accumulator register can limit the order of some operations such as matrix multiplications. Furthermore, detailed FPGA and ASIC synthesis results highlight the significant hardware cost of 64-bit posit arithmetic and quire. Despite this, the large accuracy improvements achieved with the same memory bandwidth suggest that posit arithmetic may provide a potential alternative representation for scientific computing.
On-line multi-threaded processing of web user-clicks on multi-core processors.
(High performance computing for computational science - VECPAR 2010, 2011) Bonacic, Carolina; García, Carlos; Marín, Mauricio; Prieto Matías, Manuel; Tirado Fernández, José Francisco
Medical imaging has become an absolutely essential diagnostic tool for clinical practices; at present, pathologies can be detected with an earliness never before known. Its use has not only been relegated to the field of radiology but also, increasingly, to computer-based imaging processes prior to surgery. Motion analysis, in particular, plays an important role in analyzing activities or behaviors of live objects in medicine. This short paper presents several low-cost hardware implementation approaches for the new generation of tablets and/or smartphones for estimating motion compensation and segmentation in medical images. These systems have been optimized for breast cancer diagnosis using magnetic resonance imaging technology with several advantages over traditional X-ray mammography, for example, obtaining patient information during a short period. This paper also addresses the challenge of offering a medical tool that runs on widespread portable devices, both on tablets and/or smartphones to aid in patient diagnostics.