18 papers · ranked by Valyu relevance
Vinson Young, Sanjay Kariyappa, Moinuddin K. Qureshi
—This paper investigates hardware-based memory compression designs to increase the memory bandwidth. When lines are compressible, the hardware can store multiple lines in a single memory location, and retrieve all these lines in a single access, thereby increasing the effective memory bandwidth. However, relocating and…
Gennady Pekhimenko
This research was sponsored by the National Science Foundation under grant numbers CNS-0720790, CCF-0953246, CCF-1116898, CNS-1423172, CCF-1212962, CNS-1320531, CCF-1147397, and CNS- 1409723, the Defense Advanced Research Projects Agency, the Semiconductor Research Corporation, the Gigascale Systems Research Center…
Feng Cheng, Cong Guo, Chiyue Wei, Junyao Zhang + 6 more
'Edward Hanson' 'Jiaqi Zhang' 'Xiaoxiao Liu' 'Hai "Helen" Li' 'Yiran Chen'] Large language models (LLMs) have demonstrated transformative capabilities across diverse artificial intelligence applications, yet their deployment is hindered by substantial memory and computational demands, especially in resource-constrained…
Esha Choukse, Michael Sullivan, Mike O’Connor, Mattan Erez + 3 more
'Jeff Pool' 'David Nellans' 'Steve Keckler'] GPUs offer orders-of-magnitude higher memory bandwidth than traditional CPU-only systems. But, their memory capacity tends to be relatively small and can not be increased by the user. This work proposes Buddy Compression, a scheme to increase both the effective GPU memory…
Kailun Jin, Yajuan Du, Mingzhe Zhang, Zhenghao Yin + 2 more
'Rachata Ausavarungnirun' 'Aiqun Liu'] Due to its non-volatility and large capacity, NVM devices gradually take place at various levels of memories. However, their limited endurance is still a big concern for large-scale data centres. Compression algorithms have been used to save NVM space and enhance the efficiency of…
Dale Zhou, Sharon M. Noh, Nora C. Harhen, Nidhi V. Banavar + 3 more
The ability to discriminate similar visual stimuli has been used as an important index of memory function. This ability is widely thought to be supported by expanding the dimensionality of relevant neural codes, such that neural representations for the similar stimuli are maximally distinct, or “separated.” An…
David G. Nagy, Balázs Török, Gergő Orbán
It has extensively been documented that human memory exhibits a wide range of systematic distortions, which have been associated with resource constraints. Resource constraints on memory can be formalised in the normative framework of lossy compression, however traditional lossy compression algorithms result in…
Chunbin Lin, Jianguo Wang, Yannis Papakonstantinou
Data compression schemes have exhibited their importance in column databases by contributing to the high-performance OLAP (Online Analytical Processing) query processing. Existing works mainly concentrate on evaluating compression schemes for disk-resident databases as data is mostly stored on disks. With the…
Steffen Görzig
Data compaction is a new approach for lossless and lossy compression of read-only array data. The biggest advantage over existing approaches is the possibility to access compressed data without any decompression. This makes data compaction most suitable for systems that could currently not apply compression techniques…
Yulin Feng, Yizhou Zhang, Zheng Zhou, Peng Huang + 3 more
'Xiaoyan Liu' 'Jinfeng Kang'] The exponential growth of various complex images is putting tremendous pressure on storage systems. Here, we propose a memristor-based storage system with an integrated near-storage in-memory computing-based convolutional autoencoder compression network to boost the energy efficiency and…
Puguang Liu, Ziling Wei, Chuan Yu, Shuhui Chen + 1 more
Lossless data compression is a crucial and computing-intensive application in data-centric scenarios. To reduce the CPU overhead, FPGA-based accelerators have been proposed to offload compression workloads. However, most existing schemes have the problem of an imbalanced resource utilization and a poor practicability.…
Yicong Li, Core Francisco Park, Daniel Xenes, Caitlyn Bishop + 7 more
The ongoing pursuit to map detailed brain structures at high resolution using electron microscopy (EM) has led to advancements in imaging that enable the generation of connectomic volumes that have reached the petabyte scale and are soon expected to reach the exascale for whole mouse brain collections. To tackle the…
M Baritha Begum, N. Deepa, Mueen Uddin, Rajesh Kaluri + 2 more
'Maha Abdelhaq' 'Raed Alsaqour'] Data stored on physical storage devices and transmitted over communication channels often have a lot of redundant information, which can be reduced through compression techniques to conserve space and reduce the time it takes to transmit the data. The need for adequate security…
David Podgorelec, Damjan Strnad, Ivana Kolingerová, Borut Žalik + 1 more
'Jun Chen'] After a boom that coincided with the advent of the internet, digital cameras, digital video and audio storage and playback devices, the research on data compression has rested on its laurels for a quarter of a century. Domain-dependent lossy algorithms of the time, such as JPEG, AVC, MP3 and others…
Miaoshan Lu, Junjie Tong, Ruimin Wang, Shaowei An + 2 more
Mass spectrum (MS) data volumes increase with an improved ion acquisition ratio and a highly accurate mass spectrometer. However, the most widely used data format, mzML, does not take advantage of compression methods and improved read performances. Several compression algorithms have been proposed in recent years, and…
Vlad-Ilie Ungureanu, Paul Negirla, Adrian Korodi, Attilio Di Nisio + 1 more
'Gwanggil Jeon'] Image compression is a vital component for domains in which the computational resources are usually scarce such as automotive or telemedicine fields. Also, when discussing real-time systems, the large amount of data that must flow through the system can represent a bottleneck. Therefore, the storage of…
Anas Al-okaily, Abdelghani Tbakhi
Data compression is a challenging and increasingly important problem. As the amount of data generated daily continues to increase, efficient transmission and storage has never been more critical. In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and associated…
Daniel Probst
Last year, a preprint gained notoriety, proposing that a k-nearest neighbour classifier is able to outperform large-language models using compressed text as input and normalised compression distance (NCD) as a metric. In chemistry and biochemistry, molecules are often represented as strings, such as SMILES for small…