Demo Data from SIGIR 2026 / reviewers in the wild / expert
Bhushan Chitlur
dblp:95/9034 · also Chitlur Nagabhushan, Nagabhushan Chitlur
· DBLP profile ↗
6ranked-venue papers
1as first author
2since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 5 · 1 first-author · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 since 2021
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
5 papers |
Memory systems · 47% Cloud and datacenter computing · 16% Hardware accelerators and domain-specific architectures · 16% | |
| Computer networks
1 paper |
Internet architecture and protocols · 100% |
Topics — the 14 heaviest of 18, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Hardware accelerators and domain-specific architectures › domain-specific accelerator
compression accelerator |
0.8 | 1 | 2024 | Sabre: Hardware-Accelerated Snapshot Compression for Serverless MicroVMs · OSDI 2024 |
Memory systems › memory disaggregation
CXL memory |
0.8 | 1 | 2024 | Demystifying a CXL Type-2 Device: A Heterogeneous Cooperative Computing Perspective · MICRO 2024 |
Memory systems › memory management
memory deduplication |
0.8 | 1 | 2024 | Demystifying a CXL Type-2 Device: A Heterogeneous Cooperative Computing Perspective · MICRO 2024 |
Memory systems
memory optimization |
0.8 | 1 | 2024 | Demystifying a CXL Type-2 Device: A Heterogeneous Cooperative Computing Perspective · MICRO 2024 |
Cloud and datacenter computing
serverless computing |
0.8 | 1 | 2024 | Sabre: Hardware-Accelerated Snapshot Compression for Serverless MicroVMs · OSDI 2024 |
Performance modeling and evaluation › benchmarking
microbenchmarking |
0.2 | 1 | 2024 | Demystifying a CXL Type-2 Device: A Heterogeneous Cooperative Computing Perspective · MICRO 2024 |
Processor architecture and microarchitecture › multicore design › heterogeneous multicore
asymmetric multicore |
0.1 | 1 | 2012 | QuickIA: Exploring heterogeneous architectures on real prototypes · HPCA 2012 |
Electronic design automation
design space exploration |
0.1 | 1 | 2012 | QuickIA: Exploring heterogeneous architectures on real prototypes · HPCA 2012 |
GPUs and heterogeneous computing
heterogeneous architecture |
0.1 | 1 | 2012 | QuickIA: Exploring heterogeneous architectures on real prototypes · HPCA 2012 |
Reconfigurable computing and FPGAs
FPGA accelerator |
0.1 | 1 | 2009 | High-performance, energy-efficient platforms using in-socket FPGA accelerators · FPGA 2009 |
Internet architecture and protocols › local area network
ethernet |
0.1 | 1 | 2007 | High-performance ethernet-based communications for future multi-core processors · SC 2007 |
Internet architecture and protocols
network interface card |
0.1 | 1 | 2007 | High-performance ethernet-based communications for future multi-core processors · SC 2007 |
Memory systems
cache coherence |
0.0 | 1 | 2009 | High-performance, energy-efficient platforms using in-socket FPGA accelerators · FPGA 2009 |
Interconnection networks and networks-on-chip
cluster interconnect |
0.0 | 1 | 2007 | High-performance ethernet-based communications for future multi-core processors · SC 2007 |
Methods — techniques the papers use, named apart from their topics
microbenchmarking · 0.8hardware acceleration · 0.8prototyping · 0.1hardware-software co-design · 0.1case study · 0.1dynamic FPGA reprogramming · 0.1accelerator abstraction layer · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Demystifying a CXL Type-2 Device: A Heterogeneous Cooperative Computing PerspectiveabstractCXL is the latest interconnect technology built on PCIe, providing three protocols to facilitate three distinct types of devices, each with unique capabilities. Among these devices, a CXL Type-2 device has become commercially available, followed by CXL Type-3 devices. Therefore, it is timely to understand capabilities and characteristics of the CXL Type-2 device, as well as explore suitable applications. In this work, first, we delve into three key features of a CXL Type-2 device: cache-coherent device accelerator to host memory, device accelerator to device memory, and host CPU to device memory accesses. Second, using microbenchmarks, we comprehensively characterize the latency and bandwidth of these memory accesses with a CXL Type-2 device, and then compare them with those of equivalent memory accesses with comparable devices, such as emulated CXL Type-2, CXL Type-3, and PCIe devices. Lastly, as applications that exploit the unique capabilities of a CXL Type-2 device, we propose two CXL-based Linux memory optimization features: compressed RAM cache for swap (zswap) and memory deduplication (ksm). Our evaluation shows that Redis, when running with traditional CPU-based zswap and ksm, suffers from a tail latency increase of 4.5-10.3× compared to Redis running alone. While PCIe-based zswap and ksm still experience a tail latency increase of up to 8.1×, CXL-based zswap and ksm practically eliminate the tail latency increase with faster and more efficient host-device communication than PCIe-based zswap and ksm. Houxiang Ji, Srikar Vanavasam, Yang Zhou 0050, Qirong Xia, Jinghan Huang 0001, Ren Wang 0001, Pekon Gupta, Bhushan Chitlur, Ipoom Jeong, Nam Sung Kim |
MICRO | 9 |
| 2024 | Sabre: Hardware-Accelerated Snapshot Compression for Serverless MicroVMs
Nikita Lazarev, Varun Gohil, James Tsai, Andy Anderson, Bhushan Chitlur, Zhiru Zhang, Christina Delimitrou |
OSDI | 5 |
| 2012 | QuickIA: Exploring heterogeneous architectures on real prototypesabstractOver the last decade, homogeneous multi-core processors emerged and became the de-facto approach for offering high parallelism, high performance and scalability for a wide range of platforms. We are now at an interesting juncture where several critical factors (smaller form factor devices, power challenges, need for specialization, etc) are guiding architects to consider heterogeneous chips and platforms for the next decade and beyond. Exploring heterogeneous architectures is challenging since it involves re-evaluating architecture options, OS implications and application development. In this paper, we describe these research challenges and then introduce a heterogeneous prototype platform called QuickIA that enables rapid exploration of heterogeneous architectures employing multiple generations of Intel processors for evaluating the implications of asymmetry and FPGAs to experiment with specialized processors or accelerators. We also show example case studies using the QuickIA research prototype to highlight its value in conducting heterogeneous architecture, OS and applications research. Bhushan Chitlur, Ganapati Srinivasa, Scott Hahn, Dheeraj Reddy, David A. Koufaty, Paul Brett, Abirami Prabhakaran, Li Zhao 0002, Nelson Ijih, Suchit Subhaschandra, Sabina Grover, Xiaowei Jiang, Ravi R. Iyer 0001 |
HPCA | 1 |
| 2010 | An FPGA Based Hybrid Processor Emulation PlatformabstractThis paper introduces a flexible, hybrid emulation platform for processor related emulation. It is based on a modern Xeon server and FPGA. With Intel processors implemented in FPGA and plugged into the Xeon server's processor socket, and with the Xeon BIOS modified to accommodate different cores, this platform is able to boot OS and run applications while interacting with the Xeon server's native hardware components. It enables researchers to do architectural changes in FPGA and quickly evaluate their effect on the whole platform. This platform is an ideal vehicle for research on processor technology, SoC architecture, reconfigurable computing, heterogeneous core architecture, etc. Qigang Wang, Rolf Kassa, Wenbo Shen, Nelson Ijih, Bhushan Chitlur, Michael Konow, Arthur Sheiman, Prabhat Gupta |
FPL | 5 |
| 2009 | High-performance, energy-efficient platforms using in-socket FPGA acceleratorsabstractGrowing demand for energy-efficient, high-performance systems has resulted in the growth of innovative heterogeneous computing system architectures that use FPGAs. FPGA-based architectures enable designers to implement custom instruction streams executing on potentially thousands of compute elements. Traditionally, FPGAs have been used as compute elements on PCI devices; however, this does not allow the FPGAs to be co-processors. This paper describes a high-performance system architecture that is based on the Intel® Xeon® platform in which one or more FPGAs, acting as application accelerators, replace one or more processors in a dual/multi-processor (DP/MP) platform. The FPGA is thus connected directly to the Front Side Bus (FSB) and enjoys the same privileges as a processor, i.e., full participation in the coherency protocol, unrestricted access to system memory and to other processors via the high bandwidth, and low latency connection to the FSB. In addition, we also describe a software layer called the "Accelerator Abstraction Layer (AAL)", which provides a uniform, hardware- and/or platform-independent application interface. Applications written on AAL can be ported to multiple platforms that have different types of accelerators and the application does not have to be modified. In addition, the AAL also enables the developer/user to reprogram the FPGA on the fly (analogous to an operating system context switch) thereby utilizing the programmable nature of the FPGA. The resulting hardware/software stack creates a flexible and powerful platform for accelerator innovation and deployment. Liu Ling, Neal Oliver, Bhushan Chitlur, Qigang Wang, Alvin Chen, Wenbo Shen, Zhihong Yu, Arthur Sheiman, Ian McCallum, Joseph Grecco, Henry Mitchel, Prabhat Gupta |
FPGA | 3 |
| 2007 | High-performance ethernet-based communications for future multi-core processorsabstractData centers and HPC clusters often incorporate specialized networking fabrics to satisfy system requirements. However, Ethernet's low cost and high performance are causing a shift from specialized fabrics toward standard Ethernet. Although Ethernet's low-level performance approaches that of specialized fabrics, the features that these fabrics provide such as reliable in-order delivery and flow control are implemented, in the case of Ethernet, by endpoint hardware and software. Unfortunately, current Ethernet endpoints are either slow (commodity NICs with generic TCP/IP stacks) or costly (offload engines). To address these issues, the JNIC project developed a novel Ethernet endpoint. JNIC's hardware and software were specifically designed for the requirements of high-performance communications within future data-centers and compute clusters. The architecture combines capabilities already seen in advanced network architectures with new innovations to create a comprehensive solution for scalable and high-performance Ethernet. We envision a JNIC architecture that is suitable for most in-data-center communication needs. Mike Schlansker, Bhushan Chitlur, Erwin Oertli, Paul M. Stillwell Jr., Linda Rankin, Dennis Bradford, Richard J. Carter, Jayaram Mudigonda, Nathan L. Binkert, Norman P. Jouppi |
SC | 2 |