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Yuriy Teslyar

dblp:05/6647 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

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

Systems, architecture and hardware · 2Software 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
Reconfigurable computing and FPGAs · 53% Processor architecture and microarchitecture · 16% Parallel and multicore computing · 16%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Processor architecture and microarchitecture
chip multiprocessor
0.012007
A practical FPGA-based framework for novel CMP research · FPGA 2007
Electronic design automation
hardware emulation
0.012007
A practical FPGA-based framework for novel CMP research · FPGA 2007
Parallel and multicore computing
transactional memory
0.012007
A practical FPGA-based framework for novel CMP research · FPGA 2007

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

transactional memory · 0.1FPGA prototyping · 0.1
YearPublicationVenuePosition
2007 ATLAS: a chip-multiprocessor with transactional memory support
abstract
Chip-multiprocessors are quickly becoming popular in embedded systems. However, the practical success of CMPs strongly depends on addressing the difficulty of multithreaded application development for such systems. Transactional memory (TM) promises to simplify concurrency management in multithreaded applications by allowing programmers to specify coarse-grain parallel tasks, while achieving performance comparable to fine-grain lock-based applications. This paper presents ATLAS, the first prototype of a CMP with hardware support for transactional memory. ATLAS includes 8 embedded PowerPC cores that access coherent shared memory in a transactional manner. The data cache for each core is modified to support the speculative buffering and conflict detection necessary for transactional execution. The authors have mapped ATLAS to the BEE2 multi-FPGA board to create a full-system prototype that operates at 100MHz, boots Linux, and provides significant performance and ease-of-use benefits for a range of parallel applications. Overall, the ATLAS prototype provides an excellent framework for further research on the software and hardware techniques necessary to deliver on the potential of transactional memory
Njuguna Njoroge, Jared Casper, Sewook Wee, Yuriy Teslyar, Daxia Ge, Christoforos E. Kozyrakis, Kunle Olukotun
DATE4
2007 A practical FPGA-based framework for novel CMP research
abstract
Chip-multiprocessors are quickly gaining momentum in all segments of computing. However, the practical success of CMPs strongly depends on addressing the difficulty of multithreaded application development. To address this challenge, it is necessary to co-develop new CMP architecture with novel programming models. Currently, architecture research relies on software simulators which are too slow to facilitate interesting experiments with CMP software without using small datasets or significantly reducing the level of detail in the simulated models. An alternative to simulation is to exploit the rich capabilities of modern FPGAs to create FPGA-based platforms for novel CMP research. This paper presents ATLAS, the first prototype for CMPs with hardware support for Transactional Memory (TM), a technology aiming to simplify parallel programming. ATLAS uses the BEE2 multi-FPGA board to provide a system with 8 PowerPC cores that run at 100MHz and runs Linux. ATLAS provides significant benefits for CMP research such as 100x performance improvement over a software simulator and good visibility that helps with software tuning and architectural improvements. In addition to presenting and evaluating ATLAS, we share our observations about building a FPGA-based framework for CMP research. Specifically, we address issues such as overall performance, challenges of mapping ASIC-style CMP RTL on to FPGAs, software support, the selection criteria for the base processor, and the challenges of using pre-designed IP libraries.
Sewook Wee, Jared Casper, Njuguna Njoroge, Yuriy Teslyar, Daxia Ge, Christoforos E. Kozyrakis, Kunle Olukotun
FPGA4