Mattan Erez

Sequoia: programming the memory hierarchy

We present Sequoia, a programming language designed to facilitate the development of memory hierarchy aware parallel programs that remain portable across modern machines featuring different memory hierarchy configurations. Sequoia abstractly exposes hierarchical memory in the programming model and provides language mechanisms to describe communication vertically through the machine and to localize computation to particular memory locations within it. We have implemented a complete programming system, including a compiler and runtime systems for cell processor-based blade systems and distributed memory clusters, and demonstrate efficient performance running Sequoia programs on both of these platforms

Merrimac: Supercomputing with Streams

Merrimac uses stream architecture and advanced interconnection networks to give an order of magnitude more performance per unit cost than cluster-based scientific computers built from the same technology. Organizing the computation into streams and exploiting the resulting locality using a register hierarchy enables a stream architecture to reduce the memory bandwidth required by representative applications by an order of magnitude or more. Hence a processing node with a fixed bandwidth (expensive) can support an order of magnitude more arithmetic units (inexpensive). This in turn allows a given level of performance to be achieved with fewer nodes (a 1-PFLOPS machine, for example, with just 8,192 nodes) resulting in greater reliability, and simpler system management. We sketch the design of Merrimac, a streaming scientific computer that can be scaled from a

Speculation techniques for improving load related instruction scheduling

20K 2 TFLOPS workstation to a

FREE-p: Protecting non-volatile memory against both hard and soft errors

20M 2 PFLOPS supercomputer and present the results of some initial application experiments on this architecture.

Addressing failures in exascale computing

State of the art microprocessors achieve high performance by executing multiple instructions per cycle. In an out-of-order engine, the instruction scheduler is responsible for dispatching instructions to execution units based on dependencies, latencies, and resource availability. Most existing instruction schedulers are doing a less than optimal job of scheduling memory accesses and instructions dependent on them, for the following reasons:• Memory dependencies cannot be resolved prior to execution, so loads are not advanced ahead of preceding stores.• The dynamic latencies of load instructions are unknown, so scheduling dependent instructions is based on either optimistic load-use delay (may cause re-scheduling and re-execution) or pessimistic delay (creating unnecessary delays).• Memory pipelines are more expensive than other execution units, and as such, are a scarce resource. Currently, an increase in the memory execution bandwidth is usually achieved through multi-banked caches where bank conflicts limit efficiency.In this paper we present three techniques to address these scheduler limitations. One is to improve the scheduling of load instructions by using a simple memory disambiguation mechanism. The second is to improve the scheduling of load dependent instructions by employing a Data Cache Hit-Miss Predictor to predict the dynamic load latencies. And the third is to improve the efficiency of load scheduling in a multi-banked cache through Cache-Bank Prediction.

Memory mapped ECC: low-cost error protection for last level caches

Emerging non-volatile memories such as phase-change RAM (PCRAM) offer significant advantages but suffer from write endurance problems. However, prior solutions are oblivious to soft errors (recently raised as a potential issue even for PCRAM) and are incompatible with high-level fault tolerance techniques such as chipkill. To additionally address such failures requires unnecessarily high costs for techniques that focus singularly on wear-out tolerance. In this paper, we propose fine-grained remapping with ECC and embedded pointers (FREE-p). FREE-p remaps fine-grained worn-out NVRAM blocks without requiring large dedicated storage. We discuss how FREE-p protects against both hard and soft errors and can be extended to chipkill. Further, FREE-p can be implemented purely in the memory controller, avoiding custom NVRAM devices. In addition to these benefits, FREE-p increases NVRAM lifetime by up to 26% over the state-of-the-art even with severe process variation while performance degradation is less than 2% for the initial 7 years.

Balancing DRAM locality and parallelism in shared memory CMP systems

We present here a report produced by a workshop on ‘Addressing failures in exascale computing’ held in Park City, Utah, 4–11 August 2012. The charter of this workshop was to establish a common taxonomy about resilience across all the levels in a computing system, discuss existing knowledge on resilience across the various hardware and software layers of an exascale system, and build on those results, examining potential solutions from both a hardware and software perspective and focusing on a combined approach. The workshop brought together participants with expertise in applications, system software, and hardware; they came from industry, government, and academia, and their interests ranged from theory to implementation. The combination allowed broad and comprehensive discussions and led to this document, which summarizes and builds on those discussions.

Virtualized and flexible ECC for main memory

This paper presents a novel technique, Memory Mapped ECC, which reduces the cost of providing error correction for SRAM caches. It is important to limit such overheads as processor resources become constrained and error propensity increases. The continuing decrease in SRAM cell size and the growing capacity of caches increases the likelihood of errors in SRAM arrays. To address this, redundant information can be used to correct a value after an error occurs. Information redundancy is typically provided through error-correcting codes (ECC), which append bits to every SRAM row and increase the arrays area and energy consumption. We make three observations regarding error protection and utilize them in our architecture: (1) much of the data in a cache is replicated throughout the hierarchy and is inherently redundant; (2) error-detection is necessary for every cache access and is cheaper than error correction, which is very infrequent; (3) redundant information for correction need not be stored in high-cost SRAM. Our unique architecture only dedicates SRAM for error detection while the ECC bits are stored within the memory hierarchy as data. We associate a physical memory address with each cache line for ECC storage and rely on locality to minimize the impact. The cache is dynamically and transparently partitioned between data and ECC with the fraction of ECC growing with the number of dirty cache lines. We show that this has little impact on both performance (1.3% average and < 4%) and memory traffic (3%) across a range of memory-intensive applications.

Compilation for explicitly managed memory hierarchies

Modern memory systems rely on spatial locality to provide high bandwidth while minimizing memory device power and cost. The trend of increasing the number of cores that share memory, however, decreases apparent spatial locality because access streams from independent threads are interleaved. Memory access scheduling recovers only a fraction of the original locality because of buffering limits. We investigate new techniques to reduce inter-thread access interference. We propose to partition the internal memory banks between cores to isolate their access streams and eliminate locality interference. We implement this by extending the physical frame allocation algorithm of the OS such that physical frames mapped to the same DRAM bank can be exclusively allocated to a single thread. We compensate for the reduced bank-level parallelism of each thread by employing memory sub-ranking to effectively increase the number of independent banks. This combined approach, unlike memory bank partitioning or sub-ranking alone, simultaneously increases overall performance and significantly reduces memory power consumption.

A QoS-aware memory controller for dynamically balancing GPU and CPU bandwidth use in an MPSoC

We present a general scheme for virtualizing main memory error-correction mechanisms, which map redundant information needed to correct errors into the memory namespace itself. We rely on this basic idea, which increases flexibility to increase error protection capabilities, improve power efficiency, and reduce system cost; with only small performance overheads. We augment the virtual memory system architecture to detach the physical mapping of data from the physical mapping of its associated ECC information. We then use this mechanism to develop two-tiered error protection techniques that separate the process of detecting errors from the rare need to also correct errors, and thus save energy. We describe how to provide strong chipkill and double-chip kill protection using existing DRAM and packaging technology. We show how to maintain access granularity and redundancy overheads, even when using ×8 DRAM chips. We also evaluate error correction for systems that do not use ECC DIMMs. Overall, analysis of demanding SPEC CPU 2006 and PARSEC benchmarks indicates that performance overhead is only 1% with ECC DIMMs and less than 10% using standard Non-ECC DIMM configurations, that DRAM power savings can be as high as 27%, and that the system energy-delay product is improved by 12% on average.