Physical Cores Research Articles

Lok-Test and Capo-Test pullout for in-situ concrete strength

Among the test systems for in-place concrete strength available today, two measure the in-place physical strength, pullout, and cores. Both systems are dealt with in detail in this paper, the pullout systems named LOK-TEST/CAPO-TEST (ASTM C900-19) and coring (ASTM C42/42M-18). Testing in-situ with accurate test systems will reveal effects on the final strength from a potential mix’s over transportation, pumping, consolidation, compaction, and curing. With the LOK-TEST system testing of the pre-installed inserts takes 4–5 minutes each, easily and with only one small suitcase brought along. The CAPO-TEST, originally designed to supplement the LOK-TEST, takes 15–20 minutes for each test to be performed anywhere on a structure without pre-installed inserts. No large holes are left in the structure from coring and thinner elements may be tested without weakening them structurally. The pullout test provides accurately the In-Place Strength without testing cores and the duration is about 15 minutes compared to 3–4 days for coring correctly cured. General robust correlations to strength of standard specimens exist no matter what parameter is considered for normal concrete, even for carbonation of the surface layer. With the systems the cover layer protecting the reinforcement may be checked efficiently and quickly, not at least in areas with dense reinforcement or on slim structures. Bad curing conditions are revealed and the consequences in terms of reduced service life for presence of chlorides or carbonation may be estimated swiftly. This paper is benchmarking 50 years of successful in-situ concrete strength measurements, from studies of the failure mechanism and laboratory/on-site correlations to full scale testing of structures in Europe, Scandinavia, and Canada. Six testing cases with emphasis on pullout and cores are illustrating different applications: Case 1. Production testing at the Great Belt Link, Denmark. Case 2. Service life of bridge pier, Great Belt Link, Denmark. Case 3. Curing of the cover layer evaluated by pullout and conductivity, Denmark. Case 4. Strength testing with CAPO-TEST for further loading of old bridges, Poland. Case 5. In-Situ compressive strength testing of quarantined precast concrete tunnel lining segments using CAPO-TEST, UK. Case 6. Safe and early loading with LOK-TEST, Canada. Other cases are given on www.NDTitans.com

Optimized thread-block arrangement in a GPU implementation of a linear solver for atmospheric chemistry mechanisms

Earth system models (ESM) demand significant hardware resources and energy consumption to solve atmospheric chemistry processes. Recent studies have shown improved performance from running these models on GPU accelerators. Nonetheless, there is room for improvement in exploiting even more GPU resources.This study proposes an optimized distribution of the chemical solver's computational load on the GPU, named Block-cells. Additionally, we evaluate different configurations for distributing the computational load in an NVIDIA GPU.We use the linear solver from the Chemistry Across Multiple Phases (CAMP) framework as our test bed. An intermediate-complexity chemical mechanism under typical atmospheric conditions is used. Results demonstrate a 35× speedup compared to the single-CPU thread reference case. Even using the full resources of the node (40 physical cores) on the reference case, the Block-cells version outperforms them by 50%. The Block-cells approach shows promise in alleviating the computational burden of chemical solvers on GPU architectures.

PARALLEL MESHLESS RADIAL BASIS FUNCTION COLLOCATION METHOD FOR NEUTRON DIFFUSION PROBLEMS

The meshless global radial basis function (RBF) collocation method is widely used to model physical phenomena in science and engineering. The method produces highly accurate solutions with an exponential convergence rate. However, due to the global approximation structure of the method, dense node distributions lead to long computation times and hinder the applicability of the technique. In order to overcome this issue, this study proposes a parallel meshless global RBF collocation algorithm. The algorithm is applied to 2-D neutron diffusion problems. The multiquadric is used as the RBF. The algorithm is developed with Mathematica and eight virtual processors are used in calculations on a multicore computer with four physical cores. The method provides accurate numerical results in a stable manner. Parallel speedup increases with the number of processors up to five and seven processors for external and fission source problems, respectively. The speedup values are limited by the constrained resource sharing of the multicore computer’s memory. On the other hand, significant time savings are achieved with parallel computation. For the four-group fission source problem, when 4316 interpolation nodes are employed, the utilization of seven processors instead of sequential computation decreases the computation time of the meshless approach by 716 s.

CPU Performance Study for HEP Workloads with Respect to the Number of Single-core Slots

CPU Performance Study for HEP Workloads with Respect to the Number of Single-core Slots

An efficient watermarking algorithm for digital audio data in security applications

Transform-domain audio watermarking systems are more robust than time-domain systems. However, the main weakness of these systems is their high computational cost, especially for long-duration audio signals. Therefore, they are not desirable for real-time security applications where speed is a critical factor. In this paper, we propose a fast watermarking system for audio signals operating in the hybrid transform domain formed by the fractional Charlier transform (FrCT) and the dual-tree complex wavelet transform (DTCWT). The central idea of the proposed algorithm is to parallelize the intensive and repetitive steps in the audio watermarking system and then implement them simultaneously on the available physical cores on an embedded systems cluster. In order to have a low power consumption and a low-cost cluster with a large number of physical cores, four Raspberry Pis 4B are used where the communication between them is ensured using the Message Passing Interface (MPI). The adopted Raspberry Pi cluster is also characterized by its portability and mobility, which are required in watermarking-based smart city applications. In addition to its resistance to any possible manipulation (intentional or unintentional), high payload capacity, and high imperceptibility, the proposed parallel system presents a temporal improvement of about 70%, 80%, and 90% using 4, 8, and 16 physical cores of the adopted cluster, respectively.

Identification of a novel competing endogenous RNA network and candidate drugs associated with ferroptosis in aldosterone-producing adenomas.

Aldosterone-producing adenoma (APA), characterized by unilaterally excessive aldosterone production, is a common cause of primary aldosteronism. Ferroptosis, a recently raised iron-dependent mode of programmed cell death, has been involved in the development and therapy of various diseases. This study obtained datasets of the mRNA and lncRNA expression profiles for APA and adjacent adrenal gland (AAG) from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and lncRNAs (DE lncRNAs) associated with ferroptosis were identified. Enrichment analyses indicated 89 ferroptosis-related DEGs were primarily enriched in ROS related processes and ferroptosis. Two physical cores, and one combined core were identified in the protein-protein interaction (PPI). DEGs and clinical traits were used in conjunction to screen eight hub genes from two hub modules and 89 DEGs. A competitive endogenous RNA (ceRNA) network was constructed via co-express analysis. Thereafter, molecular docking was used to identify potential targets. Two active compounds, QL-X-138 and MK-1775, bound to AURKA and DUOX1, respectively, with the lowest binding energies. Molecular dynamics simulation verified the stability of the two complexes. In summary, our studies identified eight hub genes and a novel ceRNA regulatory network associated with ferroptosis, wherein QL-X-138 and MK-1775 were considered to be potential drugs for treating APA.

EdgeMap: An Optimized Mapping Toolchain for Spiking Neural Network in Edge Computing.

Spiking neural networks (SNNs) have attracted considerable attention as third-generation artificial neural networks, known for their powerful, intelligent features and energy-efficiency advantages. These characteristics render them ideally suited for edge computing scenarios. Nevertheless, the current mapping schemes for deploying SNNs onto neuromorphic hardware face limitations such as extended execution times, low throughput, and insufficient consideration of energy consumption and connectivity, which undermine their suitability for edge computing applications. To address these challenges, we introduce EdgeMap, an optimized mapping toolchain specifically designed for deploying SNNs onto edge devices without compromising performance. EdgeMap consists of two main stages. The first stage involves partitioning the SNN graph into small neuron clusters based on the streaming graph partition algorithm, with the sizes of neuron clusters limited by the physical neuron cores. In the subsequent mapping stage, we adopt a multi-objective optimization algorithm specifically geared towards mitigating energy costs and communication costs for efficient deployment. EdgeMap-evaluated across four typical SNN applications-substantially outperforms other state-of-the-art mapping schemes. The performance improvements include a reduction in average latency by up to 19.8%, energy consumption by 57%, and communication cost by 58%. Moreover, EdgeMap exhibits an impressive enhancement in execution time by a factor of 1225.44×, alongside a throughput increase of up to 4.02×. These results highlight EdgeMap's efficiency and effectiveness, emphasizing its utility for deploying SNN applications in edge computing scenarios.

The efficiency of multithreaded computing in casting simulation software

The utilization of computer simulation software for casting process simulation is becoming essential in the advancement of casting technology in aviation and other high-tech engineering fields. With the increase in the number of computational cores in modern CPUs, the use of multi-threaded computations is becoming increasingly relevant. In this study, the efficiency of multi-threaded computations in modeling casting processes was evaluated using finite element method casting simulation software ProCast and PoligonSoft, which utilize parallel computing architectures with distributed (DMP) and shared (SMP) memory, respectively. Computations were performed on Intel and AMD-based computers, varying the number of computational threads from 4 to 32. The calculation efficiency was evaluated by measuring the calculation speed increase in the filling and solidification of GP25 castings made of ML10 alloy, as well as the complex task of filling and solidification modeling nickel superalloy casing castings with radiation heat transfer simulation. The results indicate that the minimum computation time in ProCast software is observed when using 16 computational threads. This pattern holds true for both computing systems (Intel and AMD processors), and increasing the number of threads beyond this point does not make a practical difference. The performance decrease in this scenario can be attributed to the low-performance energy-efficient cores in systems based on Intel processors or the decrease in core frequency and full loading of physical cores in systems based on AMD processors. Multi-threading the modeling task in PoligonSoft software is less efficient than in ProCast, which is a result of the shared-memory architecture used in PoligonSoft. Despite the significant difference in parallel efficiency, the task of GP25 casting solidification in both PoligonSoft and ProCast is solved in a time close enough to be considered sufficient.

Parallel Computation of Multi-GNSS and Multi-Frequency Inter-Frequency Clock Biases and Observable-Specific Biases

With the widespread application of GNSS, the delicate handling of biases among different systems and different frequencies is of critical importance, wherein the inter-frequency clock biases (IFCBs) and observable-specific signal biases (OSBs) should be carefully corrected. Usually, a serial approach is used to calculate these products. To accelerate the computation speed and reduce the time delay, a multicore parallel estimation strategy for IFCBs, code, and phase OSBs by utilizing task parallel library (TPL) is proposed, the parallel computations, including precise point positioning (PPP), IFCBs, and OSBs estimation, being carried out on the basis of data parallelisms and task-based asynchronous programming. Three weeks of observables from the multi-GNSS experiment campaign (MGEX) network is utilized. The result shows that the IFCB errors of GPS Block IIF and GLONASS M+ satellites are nonnegligible, in which the GLONASS M+ satellite R21 shows the largest IFCB of more than 0.60 m, while those of other systems and frequencies are marginal, and the code OSBs present excellent stability with a standard deviation (STD) of 0.10 ns for GPS and approximately 0.20 ns for other satellite systems. Besides, the phase OSBs of all systems show the stability of better than 0.10 ns, wherein the Galileo satellites show the best performance of 0.01 ns. Compared with the single-core serial computing method, the acceleration rates for IFCBs and OSBs estimation are 3.10, 5.53, 9.66, and 17.04 times higher using four, eight, sixteen, and thirty-two physical cores, respectively, through multi-core parallelized execution.

Architecting the Autocuckoo Filter to Defend Against Cross-Core Cache Attacks

Cross-core cache timing side-channel attacks, which observe cache access behavior of victims running on different physical cores to infer sensitive information, have become a significant threat. Although the attacks are covert, they cause the attacked cachelines to frequently migrate among cache hierarchies, rendering abnormal traffic. Based on this observation, the proposed scheme PiPoMonitor records cache-memory access traffic and prefetch suspicious lines under attack to interfere with adversaries’ probes. In pursuit of security and performance, PiPoMonitor exploits a Cuckoo filter as the recording structure and introduces two features to it: 1) autonomic deletion and 2) relocation accelerating. The former exponentially increases the uncertainty of record eviction against reverse engineering attacks, while the latter leverages a pipelined architecture to alleviate the impact of intensive filter queries on the memory critical path. PiPoMonitor is not only able to effectively mitigate cross-core cache attacks and defeat sophisticated defense-aware attackers but also induces a negligible performance penalty and acceptable hardware overhead.

Performance Assessment of Using Docker for Selected MPI Applications in a Parallel Environment Based on Commodity Hardware

In the paper, we perform detailed performance analysis of three parallel MPI applications run in a parallel environment based on commodity hardware, using Docker and bare-metal configurations. The testbed applications are representative of the most typical parallel processing paradigms: master–slave, geometric Single Program Multiple Data (SPMD) as well as divide-and-conquer and feature characteristic computational and communication schemes. We perform analysis selecting best configurations considering various optimization flags for the applications and best execution times and speed-ups in terms of the number of nodes and overhead of the virtualized environment. We have concluded that for the configurations giving the shortest execution times the overheads of Docker versus bare-metal for the applications are as follows: 7.59% for master–slave run using 64 processes (number of physical cores), 15.30% for geometric SPMD run using 128 processes (number of logical cores) and 13.29% for divide-and-conquer run using 256 processes. Finally, we compare results obtained using gcc V9 and V7 compiler versions.

Entropy Generation Parallel Analysis and Optimised Efficiency of a Wavy Solar Collector

The current paper is aimed to study entropy generation analysis and natural convective flow of -water based nanofluid filled inside wavy solar collector with right-angled triangular cross sectional area. The flow is assumed to be steady, laminar and incompressible with double diffusive convection. The set of governing equations are the conservation of mass, momentum, energy and concentration which have been solved by implementing the Parallel approach of Element free Galerkin method using parallelism of graphic processor units (GPUs) involving six physical cores (12 logical cores) of Intel® Xeon® E5645 CPUs at 2.40 GHz. The effect of various parameters namely Dufour effect, Soret effect and Schmidt number on the isotherms, iso-concentration, streamlines, average Nusselt number and Sherwood number have been studied. The results show that the waviness of the slant cover plate results in perturbation in the flow which has significant effect on the heat transfer rate because of the increased surface area. The parallel approach of the meshfree technique has improved the computational efficiency which is a novel contribution.

Characteristics of CO2 foam plugging and migration: Implications for geological carbon storage and utilization in fractured reservoirs

Fractured reservoirs exhibit heterogeneity and high conductivity, posing challenges to the application of low-carbon and clean production technologies. In this study, the flow and plugging characteristics of CO2 foam in fractured cores were analyzed in physical fracture cores and visual slab fracture models. The influence of surface roughness and fracture openings on foam flow and plugging efficiency were studied. Results show that polymer-enhanced foam displays a higher-pressure drop in a single core with a small fracture opening. With increasing fracture opening, the plugging capacity of the polymer-enhanced foam gradually decreases to that of ordinary foam. In parallel fractures of different openings, ordinary foam is better able to regulate the flow, whereas the conformance control of polymer-enhanced is more robust. Prolonged foam flow in the fractures leads to foam collapse, especially for small fracture openings and high roughness. For such a core, the difference in distance lapsed by the upper and lower ends of the polymer-enhanced foam front is greater than that of the ordinary foam, and the bubble collapse during migration is less. For a given surface roughness, the smaller the fracture opening, the greater the resistance to foam flow. However, the resistance brought forth by surface roughness is greater, for a given fracture opening. Foam flow in the fracture is analyzed in terms of the forces acting on the foam. Understanding foam flow resistance is a key to preventing gas channeling, expanding sweep range and improving the oil washing efficiency.

Enhanced Parallel Sine Cosine Algorithm for Constrained and Unconstrained Optimization

The sine cosine algorithm’s main idea is the sine and cosine-based vacillation outwards or towards the best solution. The first main contribution of this paper proposes an enhanced version of the SCA algorithm called as ESCA algorithm. The supremacy of the proposed algorithm over a set of state-of-the-art algorithms in terms of solution accuracy and convergence speed will be demonstrated by experimental tests. When these algorithms are transferred to the business sector, they must meet time requirements dependent on the industrial process. If these temporal requirements are not met, an efficient solution is to speed them up by designing parallel algorithms. The second major contribution of this work is the design of several parallel algorithms for efficiently exploiting current multicore processor architectures. First, one-level synchronous and asynchronous parallel ESCA algorithms are designed. They have two favors; retain the proposed algorithm’s behavior and provide excellent parallel performance by combining coarse-grained parallelism with fine-grained parallelism. Moreover, the parallel scalability of the proposed algorithms is further improved by employing a two-level parallel strategy. Indeed, the experimental results suggest that the one-level parallel ESCA algorithms reduce the computing time, on average, by 87.4% and 90.8%, respectively, using 12 physical processing cores. The two-level parallel algorithms provide extra reductions of the computing time by 91.4%, 93.1%, and 94.5% with 16, 20, and 24 processing cores, including physical and logical cores. Comparison analysis is carried out on 30 unconstrained benchmark functions and three challenging engineering design problems. The experimental outcomes show that the proposed ESCA algorithm behaves outstandingly well in terms of exploration and exploitation behaviors, local optima avoidance, and convergence speed toward the optimum. The overall performance of the proposed algorithm is statistically validated using three non-parametric statistical tests, namely Friedman, Friedman aligned, and Quade tests.

Effect of Hyper-Threading in Latency-Critical Multithreaded Cloud Applications and Utilization Analysis of the Major System Resources

Multithreaded latency-critical applications represent an important subset of workloads running on public cloud systems. Most of these systems deploy powerful computing servers including Intel Hyper-Threading processors. Understanding how performance is affected by the consumption of the main system resources is a major concern for cloud providers in order to devise virtualization strategies that improve the system efficiency. With this aim, this paper first characterizes the impact of QPS on tail latency, analyzing different scenarios varying the number of threads and the thread-to-core allocation (single-task and multi-task execution) policy. The characterization study reveals that the performance of some applications does not scale with the number of threads, and the performance of some others is insensitive to the Hyper-Threading technology, so they can be allocated in less physical cores and improve system utilization. Identifying these applications, however, at run-time is challenging. Despite identifying these applications at run-time is challenging, this paper shows that they can be successfully detected at run-time by analyzing the utilization trend of the major system resources. In addition to CPU, we have also studied how assigning the share of each application of other major shared system resources impacts on performance. We outline considerations cloud providers should take into account to improve performance and resource utilization.

Formal Specification and Verification of Data Separation for Muen Separation Kernel

Introduction: Development of integrated mixed-criticality systems is becoming increasingly popular for application-specific systems, which needs separation mechanism for available onboard resources and the processors equipped with hardware virtualization. Hardware virtualization allow the partitions to physical resources, which include processor cores, memory, and I/O devices, among guest virtual machines (VMs). For building mixed criticality computing environment, traditional virtual machine systems are inappropriate because they use hypervisors to schedule separate VMs on physical processor cores. In this article, we discuss the design of an environment for mixed-criticality systems: The Muen an x86/64 separation kernel for high assurance. The Muen Separation Kernel is an Open Source microkernel which has no runtime errors at the source code level. The Muen separation kernel has been designed precisely to encounter the challenging requirements of high-assurance systems built on the Intel x86/64 platform. Muen is under active development, and none of the kernel properties of it has been verified yet. In this paper, we present a novel work of verifying one of the kernel properties formally. Method: The CTL used in NuSMV is a first-order modal along with data-depended processes and regular formulas. CTL is a branching-time logic, meaning that its model of time is a tree-like structure in which the future is not determined; there are different paths in the future, any one of which might be an actual path that is realized . This section shows the verification of all the requirements mentioned in section 3. In NuSMV tool the command used for verification of the formulas written in CTL is checkctlspec -p ”CTL-expression”. The nearest quantifier binds each occurrence of a variable in the scope of the bound variable, which has the same name and the same number of arguments. Result: Formal methods have been applied to various projects for specification and verification purpose. Some of them are the SCOMP , SeaView , LOCK,and Multinet Gateway projects. The TLS was written formally. Several mappings were done between the TLS and the SCOMP code: Informal English language to TLS, TLS to actual code , and TLS to pseudo-code. The authors present an ACL2 model for a generic separation kernel also known as GWV approach. Conclusion: We consider the formal verification of data separation property which is one of the crucial modules to achieve the separation functionality. The verification of the data separation manager is carried out on the design level using the NuSMV tool. Furthermore, we present the complete model of the data separation unit along with its code written in the NuSMV modelling language. Finally, we have converted the non-functional requirements into the formal logic, which then has verified the model formally.

Parallel Processing Strategies for Geospatial Data in a Cloud Computing Infrastructure

This paper is on the optimization of computing resources to process geospatial image data in a cloud computing infrastructure. Parallelization was tested by combining two different strategies: image tiling and multi-threading. The objective here was to get insight on the optimal use of available processing resources in order to minimize the processing time. Maximum speedup was obtained when combining tiling and multi-threading techniques. Both techniques are complementary, but a trade-off also exists. Speedup is improved with tiling, as parts of the image can run in parallel. But reading part of the image introduces an overhead and increases the relative part of the program that can only run in serial. This limits speedup that can be achieved via multi-threading. The optimal strategy of tiling and multi-threading that maximizes speedup depends on the scale of the application (global or local processing area), the implementation of the algorithm (processing libraries), and on the available computing resources (amount of memory and cores). A medium-sized virtual server that has been obtained from a cloud service provider has rather limited computing resources. Tiling will not only improve speedup but can be necessary to reduce the memory footprint. However, a tiling scheme with many small tiles increases overhead and can introduce extra latency due to queued tiles that are waiting to be processed. In a high-throughput computing cluster with hundreds of physical processing cores, more tiles can be processed in parallel, and the optimal strategy will be different. A quantitative assessment of the speedup was performed in this study, based on a number of experiments for different computing environments. The potential and limitations of parallel processing by tiling and multi-threading were hereby assessed. Experiments were based on an implementation that relies on an application programming interface (API) abstracting any platform-specific details, such as those related to data access.

Parallel Louvain Community Detection Algorithm Based on Dynamic Thread Assignment on Graphic Processing Unit

Background and Objectives: Louvain is a time-consuming community detection algorithm especially in large-scale networks. Using Graphic Processing Unit (GPU) in order to calculate modularity sigma, which is a major processing section in Louvain algorithm, can reduce algorithm execution time and make it practical for large-scale networks.Methods: The proposed algorithm Dynamic CUDA Louvain Method (DCLM) blocks hardware threads dynamically on cores inside GPU. By considering the properties of GPU, this algorithm allocates the maximal number of processing cores to each Stream Multi-Processor (SM) as number of threads in a block. If the number of nodes in the graph is smaller than all physical cores on GPU, number of threads per block Is equal to the ratio number of graph nodes over the number of SMs.Results: The implementation results demonstrated that the proposed algorithm is able to decrease the run time by 15% in comparison with the best past method in the large-scale graph.Conclusion: We have introduced DCLM algorithm based on GPU that accelerates Louvain community detection algorithm. Dynamic allocation of threads to each block has a significant effect on the reduction of algorithm execution time. However, incrementing the number of threads per block alone does not result to acceleration the speed of calculations.

Future-Based Persistent Spatial Data Structure for NVM-Based Manycore Machines

R-trees have been popular for their support of multidimensional data and high-performing queries. FBR-tree is the state-of-the-art concurrent variant of the R-tree for Intel DC Persistent Memory (DCPM). However, its adoption on manycore servers is impeded by concurrency limitations due to lengthy, lock-based synchronization, including structure modification operations, split and merge. Additionally, emerging DCPM-based machines are equipped with multiple CPU sockets, forming a non-uniform memory access (NUMA) architecture. FBR-tree’s lack of NUMA-awareness induces further performance overhead from remote memory accesses. In this paper, we propose MPR-tree, a concurrent, NUMA-aware and persistent future-based R-tree for DCPM servers. MPR-tree focuses on insert operations due to their laborious nature. MPR-tree relies on per-thread local future objects and a global R-tree. To introduce NUMA-awareness and minimize remote memory accesses, MPR-tree adopts per-socket dedicated asynchronous evaluate threads to checkpoint future objects to the global R-tree. MPR-tree employs an in-memory hash table to mitigate the read overhead of key searches over the future objects. We implemented MPR-tree atop FBR-tree and evaluated its performance on a server with 40 physical cores for insert and lookup queries, and it showed that MPR-tree outperforms FBR-tree on average by 2× on log10 scale.

Apercal—The Apertif calibration pipeline

Apertif (APERture Tile In Focus) is one of the Square Kilometre Array (SKA) pathfinder facilities. The Apertif project is an upgrade to the 50-year-old Westerbork Synthesis Radio Telescope (WSRT) using phased-array feed technology. The new receivers create 40 individual beams on the sky, achieving an instantaneous sky coverage of 6.5 square degrees. The primary goal of the Apertif Imaging Survey is to perform a wide survey of 3500 square degrees (AWES) and a medium deep survey of 350 square degrees (AMES) of neutral atomic hydrogen (up to a redshift of 0.26), radio continuum emission and polarisation. Each survey pointing yields 4.6 TB of correlated data. The goal of Apercal is to process this data and fully automatically generate science ready data products for the astronomical community while keeping up with the survey observations. We make use of common astronomical software packages in combination with Python based routines and parallelisation. We use an object oriented module-based approach to ensure easy adaptation of the pipeline. A Jupyter notebook based framework allows user interaction and execution of individual modules as well as a full automatic processing of a complete survey observation. If nothing interrupts processing, we are able to reduce a single pointing survey observation on our five node cluster with 24 physical cores and 256 GB of memory each within 24h keeping up with the speed of the surveys. The quality of the generated images is sufficient for scientific usage for 44 % of the recorded data products with single images reaching dynamic ranges of several thousands. Future improvements will increase this percentage to over 80 %. Our design allowed development of the pipeline in parallel to the commissioning of the Apertif system.