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Accelerating Large Table Scan Using Processing-In-Memory Technology
Today’s systems are capable of storing large amounts of data in main memory. Particularly, in-memory DBMSs benefit from this development. However,...
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Temporal Graph Processing in Modern Memory Hierarchies
Updates in graph DBMS lead to structural changes in the graph over time with different intermediate states. These intermediate states in a DBMS and...
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Efficient memory reuse methodology for CNN-based real-time image processing in mobile-embedded systems
Real-time image processing applications such as intelligent security and traffic management requires pattern recognition tasks, such face...
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COPPER: a combinatorial optimization problem solver with processing-in-memory architecture
The combinatorial optimization problem (COP), which aims to find the optimal solution in discrete space, is fundamental in various fields....
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Optimization of OLAP In-Memory Database Management Systems with Processing-In-Memory Architecture
With the growing popularity of Processing-In-Memory (PIM) technology, many sectors of the industry are willing to take advantage of this new...
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Attractor Properties of Spatiotemporal Memory in Effective Sequence Processing Task
AbstractFor autonomous AI systems, it is important to process spatiotemporal information to encode and memorize it and extract and reuse abstractions...
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Minimizing Memory Contention in an APNG Encoder Using a Grid of Processing Cells
Modern processors experience memory contention when the speed of their computational units exceeds the rate at which data can be accessed in memory....
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Energy Efficiency Impact of Processing in Memory: A Comprehensive Review of Workloads on the UPMEM Architecture
Processing-in-Memory (PIM) architectures have emerged as a promising solution for data-intensive applications, providing significant speedup by...
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Realization of processing-in-memory using binary and ternary quantum-dot cellular automata
Processing-in-memory (PIM) is a computing paradigm through which computations and processing can be performed within the memory of a computer,...
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Breaking the von Neumann bottleneck: architecture-level processing-in-memory technology
The “memory wall” problem or so-called von Neumann bottleneck limits the efficiency of conventional computer architectures, which move data from...
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PIM-Align: A Processing-in-Memory Architecture for FM-Index Search Algorithm
Genomic sequence alignment is the most critical and time-consuming step in genomic analysis. Alignment algorithms generally follow a seed-and-extend...
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Mille Cheval: a GPU-based in-memory high-performance computing framework for accelerated processing of big-data streams
Streams are temporally ordered, rapid changing, ample in volume, and infinite in nature. It is nearly impossible to store the entire data stream due...
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abstractPIM: A Technology Backward-Compatible Compilation Flow for Processing-In-Memory
The von Neumann architecture, in which the memory and the computation units are separated, demands massive data traffic between the memory and the...
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Exploiting 3D Memory for Accelerated In-Network Processing of Hash Joins in Distributed Databases
The computing potential of programmable switches with multi-Tbit/s throughput is of increasing interest to the research community and industry alike....
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Separation of Memory and Processing in Dual Recurrent Neural Networks
We explore a neural network architecture that stacks a recurrent layer and a feedforward layer, both connected to the input. We compare it to a...
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A perceptual and predictive batch-processing memory scheduling strategy for a CPU-GPU heterogeneous system
When multiple central processing unit (CPU) cores and integrated graphics processing units (GPUs) share off-chip main memory, CPU and GPU...
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Towards High-Performance Graph Processing: From a Hardware/Software Co-Design Perspective
Graph processing has been widely used in many scenarios, from scientific computing to artificial intelligence. Graph processing exhibits irregular...
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In-Memory Computing: The Integration of Storage and Processing
In today’s computer architectures, the data is processed and stored in two separate units. Therefore, a communication system is needed to transfer...
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ARCHER: a ReRAM-based accelerator for compressed recommendation systems
Modern recommendation systems are widely used in modern data centers. The random and sparse embedding lookup operations are the main performance...
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HPCache: memory-efficient OLAP through proportional caching revisited
Analytical engines rely on in-memory data caching to avoid storage accesses and provide timely responses by kee** the most frequently accessed data...
