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Haren Myneni

dblp:270/3884 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1Software engineering, systems software and programming languages · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 61% Hardware accelerators and domain-specific architectures · 30% Cloud and datacenter computing · 9%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Hardware accelerators and domain-specific architectures › domain-specific accelerator
compression accelerator
0.412020
Data Compression Accelerator on IBM POWER9 and z15 Processors : Industrial Product · ISCA 2020
Storage systems
data compression
0.412020
Data Compression Accelerator on IBM POWER9 and z15 Processors : Industrial Product · ISCA 2020
Storage systems › data compression
lossless compression
0.412020
Data Compression Accelerator on IBM POWER9 and z15 Processors : Industrial Product · ISCA 2020

Methods — techniques the papers use, named apart from their topics

on-chip integration · 0.4
YearPublicationVenuePosition
2020 Data Compression Accelerator on IBM POWER9 and z15 Processors : Industrial Product
abstract
Lossless data compression is highly desirable in enterprise and cloud environments for storage and memory cost savings and improved utilization I/O and network. While the value provided by compression is recognized, its application in practice is often limited because it's a processor intensive operation resulting low throughput and high elapsed time for compression intense workloads.The IBM POWER9 and IBM z15 systems overcome the shortcomings of existing approaches by including a novel on-chip integrated data compression accelerator. The accelerator reduces processor cycles, I/O traffic, memory and storage footprint of many applications practically with zero hardware cost. The accelerator also eliminates the cost and I/O slots that would have been necessary with FPGA/ASIC based compression adapters. On the POWER9 chip, a single accelerator uses less than 0.5% of the processor chip area, but provides a 388x speedup factor over the zlib compression software running on a general-purpose core and provides a 13x speedup factor over the entire chip of cores. On a POWER9 system, the accelerators provide an end-to-end 23% speedup to Apache Spark TPC-DS workload compared to the software baseline. The z15 chip doubles the compression rate of POWER9 resulting in even much higher speedup factors over the compression software running on general-purpose cores. On a maximally configured z15 system topology, on-chip compression accelerators provide up to 280 GB/s data compression rate, the highest in the industry. Overall, the on-chip accelerators significantly advance the state of the art in terms of area, throughput, latency, compression ratio, reduced processor utilization, power/energy efficiency, and integration into the system stack.This paper describes the architecture, and novel elements of the POWER9 and z15 compression/decompression accelerators with emphasis on trade-offs that made the on-chip implementation possible.
Bülent Abali, Bart Blaner, John J. Reilly, Matthias Klein, Craig B. Agricola, Bedri Sendir, Alper Buyuktosunoglu, Christian Jacobi 0002, William J. Starke, Haren Myneni
ISCA11