Publications by Pejman Lotfi Kamran

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Growing core counts have highlighted the need for scalable on-chip coherence mechanisms. The increase in the number of on-chip cores exposes the energy and area costs of scaling the directories. Duplicate-tag based directories require highly associative st ...

Scale-out datacenters mandate high per-server throughput to get the maximum benefit from the large TCO investment. Emerging applications (e.g., data serving and web search) that run in these datacenters operate on vast datasets that are not accommodated by ...

Scale-out server workloads benefit from many-core processor organizations that enable high throughput thanks to abundant request-level parallelism. A key characteristic of these workloads is the large instruction footprint that exceeds the capacity of priv ...

On-chip coherence directories of today’s multi-core systems are not energy efficient. Coherence directories dissipate a significant fraction of their power on unnecessary lookups when running commercial server and scientific workloads. These workloads have ...

Global-scale online services, such as Google’s Web search and Facebook’s social networking, run in large-scale datacenters. Due to their massive scale, these services are designed to scale out (or distribute) their respective loads and datasets across thou ...

We propose a power-efficient many-core server-on-chip system with 3D-stacked Wide I/O DRAM targeting cloud workloads in datacenters. The integration of 3D-stacked Wide I/O DRAM on top of a logic die increases available memory bandwidth by using dense and f ...

Performance and total cost of ownership (TCO) are key optimization metrics in large-scale data centers. According to these metrics, data centers designed with conventional server processors are inefficient. Recently introduced processors based on low-power ...

Pejman Lotfi Kamran

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Cuckoo Directory: A Scalable Directory for Many-Core Systems

Scale-Out Processors

NOC-Out: Microarchitecting a Scale-Out Processor

TurboTag: Lookup Filtering to Reduce Coherence Directory Power

Scale-Out Processors

Thermal Characterization of Cloud Workloads on a Power-Efficient Server-on-Chip

Optimizing Data-Center TCO with Scale-Out Processors