What is SAFARI?

SAFARI is the research group of Professor Onur Mutlu in the Computer Architecture Lab (CALCM) at Carnegie Mellon University. We investigate safe, fair, robust and intelligent computer architecture, finding novel ways to provide a substrate with all of these properties for next-generation multicore and manycore systems.

• Safe: We aim to provide secure execution and performance isolation to concurrently executing programs in manycore systems, minimizing the potential for starvation, denial-of-service attacks, information leakage, and hardware-based security vulnerabilities. We also investigate architectures that provide support for the development and efficient execution of secure software.


• Fair: We investigate mechanisms to provide fairness in shared-resource management, ensuring that multi-user and multi-programmed systems distribute computational power in a manner that is consistent with system's fairness and Quality of Service policies. The mechanisms we develop provide a hardware substrate the system software or the user/programmer can control to enforce a variety of quality of service mechanisms, while maximizing performance.


• Robust: Our systems should, in addition to optimizing for safety and fairness, be robust against both software and hardware faults that may occur, whether malicious or natural.


• Intelligent: We believe that the most effective approach to providing a system substrate with these properties is to combine simple, flexible hardware measurement and control mechanisms with intelligent, adaptive system software. This hardware/software approach should preserve both the performance of hardware-assisted techniques and the flexibility and capability of software-based mechanisms. Scalability, energy-efficiency, and high performance are also key concerns in an intelligent architecture, and we strive to design novel, scalable techniques that enable flexible performance/energy tradeoffs.

SAFARI News

• Jan. 2012 -- Scalable, Energy-Efficient Memory Systems: Our ICAC 2011 paper, "Memory Power Management via Dynamic Voltage/Frequency Scaling," demonstrates that memory systems which are provisioned for high performance with memory-intensive applications are often overkill for many other applications which do not require as much memory bandwidth. Running memory at a lower frequency has a minimal impact on the performance of these applications, and also allows for an operating voltage reduction, which significantly reduces memory system power and thus increases energy efficiency. We demonstrate a dynamic voltage/frequency scaling approach to increasing memory system energy efficiency which observes memory bandwidth at runtime and scales the memory frequency and voltage with this bandwidth demand. Significantly, we evaluate this on a real server platform by using memory controller timing registers in the Intel Nehalem, which replicates the effect of dynamically adjustable memory frequency. Combined with an analytical model for power savings, we show that memory power can be reduced by 10.4% on average (20.5% max in one workload) with only 0.17% on performance. You can view our slides here: pptx, pdf.


• Dec. 2011 -- Scalable Memory Systems: Our latest work on memory interference handling, "Reducing Memory Interference in Multicore Systems via Application-Aware Memory Channel Partitioning,", was presented at MICRO 2011 in Porto Alegre, Brazil. You can view our slides here.
  
  Inter-application interference at the main memory is a major impediment to individual application and system performance. Many past works, including ours, have addressed this problem by application-aware request reordering in the memory controller. This paper presents a fundamentally different alternative approach to address this problem - application-aware Memory Channel Partitioning (MCP). The key idea of MCP is to map the data of badly-interfering applications to different memory channels. MCP performs slightly better than the current best memory request scheduling policy while involving no changes to the memory controller. We also observe that inter-application interference can be mitigated even better with a combination of memory channel partitioning and request scheduling. We propose an Integrated Memory Partitioning and Scheduling (IMPS) mechanism that improves system performance over the current best memory request scheduler, while incurring minimal hardware complexity.
• Oct. 2011 -- Efficient Cache Management: Caches are critical to performance in modern microprocessors/systems. Unfortunately, not all blocks inserted into the cache are reused later, largely degrading the performance benefit of a cache. We propose a new mechanism, VTS-cache, to predict how likely it is that a missed block will be reused if it is inserted into the cache and use this prediction to decide at what location in the cache the block should be inserted. VTS-cache uses the recency of eviction of a block to predict its future reuse behavior. We provide a practical, low-cost implementation of VTS-cache, without modifying the existing cache structure. Our technical report, "Improving Cache Performance using Victim Tag Stores," describes the mechanism and shows that VTS-cache outperforms five state-of-the-art proposals.
• Oct. 2011 -- Energy-efficient Communication Substrates: We are designing and evaluating on-chip interconnects with new designs that provide high performance with very simple router hardware, and low energy and area overhead. In our recent tech report, "A High-Performance Hierarchical Ring On-Chip Interconnect with Low-Cost Routers," we show that a hierarchy of rings on-chip provides nearly the same performance as a baseline high-performance mesh network, while using very simple ring routers and minimal buffering. The key insight is to use a high-bandwidth global ring to join several smaller local rings, and connect rings with simple transfer or "bridge" routers. The global ring allows quick cross-chip journeys and alleviates interference seen in both meshes and single-ring designs. Our technical report provides solutions to ensure forward progress in such a network (i.e., avoid livelock and deadlock), and demonstrates with synthesis-based hardware modeling that such designs are practical.
• Oct. 2011 -- Energy-efficient Communication Substrates: We are investigating ways to improve the performance and energy efficiency of bufferless deflection-based on-chip interconnects further. Our recent technical report "MinBD: A Minimally-Buffered Deflection Router Approaching Conventional Buffered-Router Performance" presents a design that has nearly the performance (within 4.6%) of conventional interconnects, with large virtual-channel buffers, by using primarily deflection routing to handle contention, and only a small buffer per router to assist in high load. We show that by addressing several simple yet important bottlenecks in earlier bufferless deflection routers (using our CHIPPER work in HPCA 2011 as an example), bufferless or minimally-buffered deflection routers show very good performance and energy efficiency. Finally, this report shows that our router design principles are applicable to high-radix routers as well, and that such routers can still provide energy savings in networks where performance degradation is already addressed by data-locality mapping techniques.
• Sep. 2011 -- Heterogeneous Main Memory with New Technologies: We are designing heterogeneous main memory systems that consist of multiple memory technologies, e.g., Phase Change Memory (PCM) and DRAM, to achieve high energy efficiency and overcome DRAM technology scaling challenges. We have developed a new way of managing data placement in such a memory system with the goal of achieving the best characteristics of both PCM and DRAM technologies. The main idea of our work is to dynamically identify and place data that cause frequent row buffer miss accesses in DRAM, and data that do not in PCM. The key insight behind this approach is that data which generally hit in the row buffer can take advantage of the large memory capacity that PCM has to offer, and still be accessed as quickly as if the data were placed in DRAM. Our technical report, "Row Buffer Locality-Aware Data Placement in Hybrid Memories," describes in detail our mechanism and results.
• Feb. 2011 -- Energy-efficient Communication Substrates: Our latest work on efficient router design, "CHIPPER: A Low-complexity Bufferless Deflection Router,", was presented at HPCA 2011 in San Antonio, Texas. You can view our slides here.
  
  We are designing energy-efficient communication substrates to enable the scaling of a parallel multiprocessor to a large number of nodes under a given power budget. To this end, we are examining the design of very efficient routers. This paper designs a simple bufferless deflection router that is competitive in operating frequency with buffered routers. It solves two key issues in deflection router design, livelock freedom and packet reassembly, with simple mechanisms.
• Dec. 2010 -- Scalable Memory Controllers: Our latest memory scheduling algorithm, "Thread Cluster Memory Scheduling: Exploiting Differences in Memory Access Behavior," was presented at MICRO 2010 in Atlanta, Georgia. You can view our slides here.
  
  Memory schedulers in multi-core systems should carefully schedule memory requests from different threads to ensure high system performance and fast, fair progress of each thread. The paper provides an application-aware memory access scheduling algorithm that maximizes system throughput and fairness at the same time, outperforming all previous algorithms in both metrics. The main idea is to dynamically divide threads into two separate clusters (latency- sensitive and bandwidth-sensitive) and employ different memory request scheduling policies in each cluster such that the needs of different kinds of threads are served separately.